I Can Get There: Developing and Assessing Student Career Self-Efficacy

While pursuing a degree goes beyond enhancing job opportunities, it remains a significant aspect of the academic experience and often influences evaluations of courses and institutions. 

Course and module evaluation feedback forms can be very effective in eliciting student views in regards to learning guidance, provision of resources, clarity of assessment requirements, and relevance to programs. However, it’s important to note that while this evaluation provides valuable insights, it may not directly correlate with improved employability prospects. Even when courses contain modules dedicated to career development, it is crucial to consider aspects beyond learning outcomes, such as informational learning and even skills acquisition. 

Self-efficacy, a belief-related theory demonstrated to strongly predict success, applies to various domains, including educational attainment and enterprise development. Albert Bandura (Bandura, 1997) who initially drew attention to self-efficacy in the educational field, depicted it as the representation of an individual’s belief in their personal capability to accomplish a job or a specific set of tasks. Bandura links increased self-efficacy to specific success through greater perseverance, a positive response to challenges, and control over motivation. An important conditional aspect is Bandura’s assertion that self-efficacy analysis–and development–should be domain-specific rather than generic. It could be beneficial to undertake initiatives aimed at assessing and tracking students’ career self-efficacy, emphasizing the experiences and events that contribute to its growth.   

Bandura’s self-efficacy theory suggests there are four major drivers for building confidence to perform and persevere at a task: mastery experience, vicarious experience, verbal persuasion, and emotional arousal. 

Career modules and self-efficacy  

Many effective career modules are based around portfolios (often electronic) with components under the following themes: 

• Application process work – including targeted CVs 
• Career and personal development planning – including self-evaluations and action plans 
• Sector/position-based research – e.g. role requirements and labor market trends 

Effective career development and planning requires a goal-oriented approach. Understanding the skills and capabilities required for the target position should include both role and sector research, as well as the analysis of relevant vacancies on which the application process is focused. 

The self-evaluation aspect of career and personal development planning should involve students mapping out their progress in relevant skills and capabilities linked to the goal position. The use of models such as Conscious Competence (as depicted in Conger and Mullen, 1981) can enable students to reflect on and recognize specific instances of mastery experience. 

While confidence, as highlighted by the emphasis on self-efficacy, is crucial, it needs to be robustly based. Consequently, self-evaluations should be constructively critical, especially in terms of the current situation and goal. Therefore, a comprehensive career self-evaluation should assess the significance of identified weaknesses and strengths in achieving and being effective in the desired position. This type of focused gap analysis may be more valuable than a general self-SWOT (Strengths-Weaknesses-Opportunities-Threats); it also aligns with action planning to address development needs.  

Regarding the research components of career portfolios, we recommend that students adopt a funnel-based approach. This means starting with a general graduate labor market analysis, particularly focusing on graduate and trainee management schemes and including skills that graduate employers are looking for. Survey research conducted by employer organizations, such as the Chartered Management Institute in the UK and the US Chambers of Commerce in the USA, is valuable because it elicits employers’ perspectives. Thereafter, we propose a more targeted exploration that examines role/sector labor market intelligence supply and demand factors and the skills that are highly valued for graduates in these specific fields. Although looking at published vacancies and their job descriptions/specifications are useful, graduate career websites such as Prospects (UK) and Prosple (USA), along with their dedicated job sectors and job profiles, provide well-informed insights and developments. 

Creating a viable portfolio requires students to assess themselves in conjunction with a well-informed understanding of the work and career environment. This process can boost self-efficacy by reflecting on mastery experiences and offering positive feedback. 

Tracking tools 

Imperial College London (2023) has developed a general self-efficacy questionnaire that asks respondents to gauge their confidence levels (ranging from: not at all; slightly; somewhat; quite; extremely) in regard to their abilities, including statements such as: 

• Achieves most goals they set themselves 
• Accomplishes difficult tasks 
• Achieves outcomes important to them 
• Succeeds in most endeavors to which they apply themselves 
• Successfully overcomes many challenges 
• Continues to perform well when things are tough 

We note that several of these questions/statements overlap with one another. It is also fairly evident that these elements could be adapted or contextualized to cater to career self-efficacy for students, aligning with Bandura’s perspective that self-efficacy analysis requires the research to be domain specific. 

There have been career and occupation-focused research studies in self-efficacy, including some intricate empirical work (Abele and Spurk, 2009). Across these studies, significant ideas of relevance include self-confidence in one’s ability and progress to date, in themes of: adapting, responding, and having the resilience to deal with challenges; possessing and/or acquiring necessary skills for roles; gathering and processing information to make correct decisions regarding relevant roles; getting onto and moving forward in a trajectory path towards career success; and performing well in roles and selection processes on the way to one’s goals. We advise that these components be used in the design of tools to assess and track student career self-efficacy. 

Recent developments in career learning  

Following direction from the professional body (Advance HE/Higher Education Academy, 2017), several higher education institutions in the UK have recently implemented career-oriented initiatives. These initiatives involve the creation of graduate attribute framework schemes and graduate award schemes, often bearing the name of the individual institutions but distinct from the degree qualifications. These schemes center on students throughout their degree program evidencing acquisition of skills, capabilities, and qualities relevant to graduate employability. Many of these attributes may be developed within the programs and their assessments, while others may be pursued by activities beyond that. Examples include fortitude, criticality, presentation, personal values, and team work. 

Again, we note the potential for mastery experience reflection here, and perhaps the scope for self-efficacy tracking through such schemes. 

Conclusion 

Exploring student career self-efficacy throughout a student’s academic journey is a valuable complement to evaluating grades and assessing their progress and performance. While short-term or reactive approaches to such data may be discouraged because of career reassessment, a necessary part of development, the evidence on this may be key to shaping effective career support during degree studies, both within the curriculum and beyond. 

---

Russ Woodward has degrees in economics from the UK Universities of Cambridge and Exeter. Since 2002, he has taught on business degrees at University Centre, Grimsby: The TEC Partnership. Woodward has written a number of papers on teaching business in higher education for the UK, USA, and Australian periodicals. 

Mandy Boyd has a bachelor’s degree in business from Hull University, UK and an MBA from Anglia Ruskin University, UK. She teaches for the business and management school at the University of Lincoln, UK. For several years she taught marketing and careers modules on the business management degrees at University Centre, Grimsby, The TEC Partnership, UK, at which she was also program leader for the business with marketing degree strand.

Reece Leggett has a bachelors degree in tourism and business management, and a post graduate certificate in education from the University of Hull, UK. He has previously worked as programme leader and curriculum manager for business at TEC Partnership’s Grimsby Institute Campus and more recently business development officer at the University of Lincoln, UK, where he is now student enterprise manager & module leader.

References

Abele, Andrea E., and Daniel Spurk. “The longitudinal impact of self-efficacy and career goals on objective and subjective career success.” Journal of vocational behavior 74, no. 1 (2009): 53-62. 

Advance HE/ Higher Education Academy. Graduate Attributes Framework. (2017). Available at: https://www.advance-he.ac.uk/knowledge-hub/graduate-attributes-framework 

Bandura, Albert. Self-efficacy: The exercise of control. (1997). New York: W. H. Freeman.  

Conger, D. Stuart and Mullen, Dana. “Life skills”. International Journal for the Advancement of Counselling. 4 (4) (1981) 305–319. 

Imperial College London. Educational Self Efficacy Scale. Centre for Higher Education Research and Scholarship (2023). Available at: https://www.imperial.ac.uk/education-research/evaluation/what-can-i-evaluate/self-efficacy/tools-for-assessing-self-efficacy/general-self-efficacy-scale/ 

The post I Can Get There: Developing and Assessing Student Career Self-Efficacy   appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/educational-assessment/i-can-get-there-developing-and-assessing-student-career-self-efficacy/

ChatGPT in the Co-creation Process for Applied Research Projects

ChatGPT’s emergence and subsequent evolution as a generative artificial intelligence tool introduces new ways of assisting students with research design. Fostering research skills with undergraduate students presents opportunities and challenges for faculty to aid with drafting research plans, questions for investigation, and methods for conducting the research. While some educators rightfully voice concerns over the ethical aspects of such a tool, this article will draw on my own experiences using ChatGPT 4.0 as a tool in research project supervision. I demonstrate how to prompt ChatGPT to give useful suggestions that can be used as actionable feedback. I also discuss how to instruct students to include ChatGPT in their research methodology when using the tool to refine research questions. 

Large language models¹ 

Large language models (LLMs) like ChatGPT are complex algorithms developed through a type of machine learning called deep learning. In such a process, the algorithm is trained on large datasets of text. By learning the patterns, language, structures, and relationships between words, ChatGPT “remembers” the content in a manner that permits it to engage in human-like conversations, answer questions, create content, or write essays.  

LLMs are part of the natural language processing models of artificial intelligence that began in the 1950s with attempts to process and understand human language based on hand-coded rules and logic to interpret text. With the advent of machine learning in the 1980s, statistical models could be trained to learn patterns in text, produce decision trees, or recognize speech and classify text. Neural networks and deep learning allowed more sophisticated understandings of language. Word embedding led to better understanding of context. In the late 2010s, OpenAI’s Generative Pre-trained Transformer (GPT) and Google’s Bidirectional Encoder Representations from Transfers were developed through pre-training on massive datasets that could later be fine-tuned for specific tasks. The 2020s have seen larger, more sophisticated models like Open AI’s GPT-3.5 and GPT-4 that can perform a wide range of language tasks with little to no task-specific training.  

AI tools necessitate quality indicators 

Predictably, the flurry around ChatGPT and other AI apps has led to the creation of a number of platforms offering subscriptions for AI-based tools for research, including a browser extension that acts as a research assistant and manuscript writing tools, to give just two examples. The growth in AI-powered products resembles the emergence of Web 1.0 and 2.0 tools that followed the advent of the World Wide Web. Those tools were not just used to develop and deliver instruction, they became useful to students for their own course projects, assignments, and assessments.  

Educational organizations and universities developed quality indicators to guide in the adoption of web tools. It remains to be seen what indicators will be adopted to ensure the quality of GPT-based tools used in higher education classrooms. At minimum such indicators should consider matters such as bias in the datasets, accessibility, and whether it requires a paid subscription. The challenge will be the scale of the undertaking because the plethora of AI tools that have arisen in just one year’s time has far outstripped that of the web tools. New generation Web 3.0 tools already integrate AI, so the quality indicators we currently use will need updating and upgrading to address the AI aspects of the technology (AI and Web3: How Are They Related? | Rather Labs Careers, n.d.). Nevertheless, educators are already employing ChatGPT and other AI-assisted tools for skills enhancement in teaching and research (Crompton and Burke, 2023). 

ChatGPT as a co-creator for research 

Knowledge co-creation benefits students, enabling them to participate more easily and with greater motivation in the education process (Pocol et al., 2022). In their research projects, my students co-create at three levels: student-client, student-supervisor, and student/supervisor-AI assistant.  This three-tier creation produces a dynamic opportunity to develop knowledge that has immediate practical use for the client, as well as skill-building benefits for the student. As the supervisor, I gain insights into teaching and learning with AI-assisted tools. 

Refining research questions with ChatGPT: Supervisor use case 

Students in their last year of bachelor studies acquire an applied research project from the workforce.  As their supervisor, I guide them in the development of a research question, a research plan to conduct the research and to adopt the methods, and relevant resources to undertake the research. ChatGPT can help at any point in the research process; however, I want to share an example of how I used ChatGPT’s response to give more targeted feedback to my supervisee.  

I designed a prompt that contextualized the task by explaining I was supervising a research project. It also instructed the tool to revise the question in a way that identified a specific legal issue. 

My prompt:   
My student is completing a research project. As supervisor, I have reviewed the main research question and see that it does not adequately identify a legal problem. Evaluate the question and give three suggestions for revising the question in a way that identifies a legal issue. Here is the research question: [paste of the question.]   

ChatGPT gave a number of suggestions based on three possible approaches: a specific legal framework, a comparative approach, or a focus on a legal dispute. This was useful for framing the project and gave the student alternate frameworks for the research problem.  

One suggestion involving a specific legal framework suggested this rephrasing: “To what extent did the COVID-19 measures taken in Germany align or conflict with the constitutional right to freedom of travel under German Basic Law and international human rights treaties?” (Personal communication with ChatGPT 4.0 on December 28, 2023.) 

I used this framing to advise the student to choose one human rights covenant to use as a legal framework thereby narrowing the scope of the research and allowing it to meet the minimum word and content requirements.  

Overall, ChatGPT was instrumental in providing the type of actionable feedback that “offers a chance of closing a gap between current performance and the performance expected…” (Mamoon-Al-Bashir, Kabir, and Rahman, 2016). I could suggest the three approaches and share one of the revised research questions with the specific legal framework in my feedback to the student. 

Ethical considerations 

When suggesting the use of ChatGPT, I ask students to acknowledge its use in a footnote and to include the prompts as an annex to the document or to link them in the footnote. I also explain that using ChatGPT is part of their research method and I ask them to include a paragraph explaining how they prompted ChatGPT and how they used the results to modify their original research questions.  

The inclusion in the methodology section goes a step further than what has been suggested in literature for citing ChatGPT or acknowledging its uses (Castellanos-Gomez, 2023). My approach recognizes that ChatGPT is part of the research process as a whole and can be employed to define questions, devise research plans or even find appropriate research methodologies. Therefore, the process of how it was used should be described in the methodology section.  

Sample methodology language 
To refine and further specify the legal framework for my research, I used chatGPT4.0. I drafted a research question, then asked ChatGPT to suggest ways to make it a concrete legal inquiry. Using the suggestions given, I revised and refined my original questions. ChatGPT’s prompts and responses are attached in Annex One. 

Conclusion 

ChatGPT has proven itself valuable in formulating research questions. Supervisors can utilize responses to provide actionable feedback, allowing students to meet learning outcomes for the research project. ChatGPT not only enhances the research process but also introduces a novel approach to knowledge co-creation, where students, supervisors, and AI assistants collaborate effectively. However, this integration comes with the responsibility of acknowledging the use of ChatGPT in research methodologies, ensuring ethical compliance and transparency in academic practices. 

---

Tamara N. Lewis Arredondo serves as a senior lecturer, teacher trainer for The Hague Centre for Teaching and Learning, and researcher for the Global and Inclusive Learning Centre of Expertise at The Hague University of Applied Sciences in The Netherlands.  

References 

‘AI and Web3: How Are They Related? | Rather Labs Careers’. n.d. Accessed 27 December 2023. https://www.ratherlabs.com/blog/ai-and-web3-how-are-they-related. 

Castellanos-Gomez, Andres. 2023. ‘Good Practices for Scientific Article Writing with ChatGPT and Other Artificial Intelligence Language Models’. Nanomanufacturing 3 (2): 135–38. https://doi.org/10.3390/nanomanufacturing3020009. 

Crompton, Helen, and Diane Burke. 2023. ‘Artificial Intelligence in Higher Education: The State of the Field’. International Journal of Educational Technology in Higher Education 20 (1): 22. https://doi.org/10.1186/s41239-023-00392-8. 

Mamoon-Al-Bashir, Md, Md Rezaul Kabir, and Ismat Rahman. 2016. ‘The Value and Effectiveness of Feedback in Improving Students’ Learning and Professionalizing Teaching in Higher Education’. Journal of Education and Practice 7 (16): 38. 

Pocol, Cristina Bianca, Liana Stanca, Dan-Cristian Dabija, Ioana Delia Pop, and Sergiu Mișcoiu. 2022. ‘Knowledge Co-Creation and Sustainable Education in the Labor Market-Driven University–Business Environment’. Frontiers in Environmental Science 10. https://www.frontiersin.org/articles/10.3389/fenvs.2022.781075. 

The post ChatGPT in the Co-creation Process for Applied Research Projects  appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/teaching-with-technology-articles/chatgpt-in-the-co-creation-process-for-applied-research-projects/

Teaching Excellence Through Mindful Reflection

Reflective teaching is examining one’s beliefs about teaching and learning and determining the alignment of those beliefs with what happens within your courses (Reflective Teaching, 2021). The goal is to think critically about one’s teaching to find evidence of effective teaching as well as identifying potential areas for improvement (Palmer, 2017). The tool described here is based on the Framework for Assessing Teaching Effectiveness (FATE) and is intended to help teachers develop self-reflection around teaching and objectively describe their strengths and weaknesses in a manner consistent with the evidence of their teaching practices (Simonson, Earl, and Frary, 2021; Simonson, Frary, and Earl, 2023). 

Piaget is credited with developing the constructivist model of learning, but it is John Dewey who developed the focus on constructivism as a learning theory and the role of reflection in learning (Von Glaserfeld, 1982; Kolb, 1993).  In 1993, Kolb brought reflection to the forefront in his description of its role in experiential learning (Kolb, 1993).  Dewey and Kolb suggest that reflection is critical for learning to occur; however, it is not just students who benefit from reflection, those who teach can also benefit from reflecting about their teaching (Brookfield, 1998). 

There are many reflective tools and frameworks available. The purpose of this one is to help teachers develop self-reflection around teaching and objectively describe their strengths and weaknesses in a manner consistent with the evidence of their teaching practices.  It is comprehensive, formal, and guided as it addresses the myriad aspects of teaching as identified in the Framework for Assessing Teaching Effectiveness (FATE) (Simonson, Earl, and Frary, 2021; Simonson, Frary, and Earl, 2023). When completing the series of reflective exercises, the teacher should be able to: 

• define reflective teaching, 
• develop strategies for self-observation, 
• begin developing and/or refine tools for thinking about their teaching and their teaching effectiveness, and 
• begin or continue to develop a habit of continuous quality improvement, (i.e., professional development). 

Reflective teaching defined

Reflection has many definitions. Here, we are going to use two from the Merriam-Webster dictionary (Merriam-Webster, 2018): 

6: a thought, idea, or opinion formed, or a remark made as a result of meditation. 
7: consideration of some subject matter, idea, or purpose. 

Thus, reflective teaching is considering one’s teaching to form an opinion of teaching effectiveness and learner outcomes.  It is based on and necessitates analyzing one’s theories of teaching and learning, the alignment of these theories with the class experience, and critically assessing the student, teacher, and class experience along with successes and failures (Brookfield, 1998). Being a reflective teacher means collecting evidence about teaching and learning, thinking critically about that evidence, and drawing conclusions about teaching and learning.  Collecting, recording, and analyzing what happens in the preparation and delivery of a course helps the teacher move from just sharing information to understanding and shaping their teaching and the student learning experience.  From this, areas of success and improvement can be identified and learning outcomes improved.  By aligning this reflection with FATE, the intention is to orient the conclusions drawn with the components of effective teaching and actual classroom practices before, during, and after a course is taught. 

To become a reflective teacher, one needs to become aware of their own thinking processes and consider sources beyond themselves—this is enhanced when made transparent to others.  Doing so enables the assessment of the “why” and “how” of student learning and determines what needs to be done as a result. Brookfield (Brookfield, 1998) identifies four lenses through which to examine our teaching (figure 1 in Appendix).  Our autobiography as learners significantly shapes us as teachers because our past has created an intuitive and emotional long-lasting influence that determines how we teach. This can be difficult to change, even in the face of evidence-based practices.  Our own experiences play a role in the pedagogies and behaviors that appeal to and repel us, and it is useful to explore and become aware of these learned preferences to identify how they shape our teaching (Brookfield, 1998). However, because we are using our own “interpretive filters” to view ourselves, this is inherently biased and external input is necessary.  The lens of our learners can help us see how the intended audience receives and perceives our teaching which allows us to teach responsively. (Anonymity is critical for learners if we want their honest appraisal.)  

Understanding the learner experience allows the teacher to make informed, appropriate, and helpful pedagogical, relational, and teaching choices (Brookfield, 1998). Our colleagues’ perceptions can also prove useful as they can provide content and/or teaching-specific feedback that students may not be able to and that our own autobiographical lens may interpret differently.  In addition, learning how our peers handle similar situations can broaden our perspective and expose us to new strategies.  There is also an emotional benefit to knowing that others have similar experiences and commiserating that can change power dynamics (Brookfield, 1998). Lastly, the theoretical, philosophical, and research literature can prove useful in making sense of our experience and observations.  It names our experiences and provides an evidence-based alternative perspective to our autobiographical lens (Brookfield, 1998). 

In his 1993 experiential learning discussion, Kolb describes how reflection impacts learning and behavior and the cyclical nature of it (Kolb, 1993). This applies to the growth of teachers as well. According to Kolb, learning is the modification of ideas or concepts based on experience and occurs when the incongruity between observations and expectations is considered and resolved.  This process is cyclical in nature in that we experience an event, we interpret that event based on our past experiences and expectations, and we identify how that event met or did not meet our expectations. We then think about and modify our expectations and our behaviors for the next time that event occurs, and we repeat the cycle (figure 2) (Kolb, 1993).  For example, a teacher leads an in-class discussion in which the majority of students are hesitant to participate.  Based on prior experience and this teacher’s own autobiography as a learner, they may interpret this as students being unprepared.  They then reflect and explore options for increasing student preparation and institute a pre-class readiness quiz.  They then lead the class in another discussion and observe the level of participation and reflect on the level of success. 

Just like with our students, a growth mindset enhances reflection, and there are attitudes and behaviors that engender this mindset.  The reflective educator should have self-acceptance with a desire to improve, patience with themselves and their students, the organizational and time-management skills to incorporate reflection, and the ability to self-analyze and identify their strengths, weaknesses, goals, and challenges (Leon-Henri, 2020). From here, a framework on which to build reflection skills is useful.  The reflection tool provided in the Appendix is based on a reflection tool developed by the Danielson group and aligned with the FATE definition of effective teaching (Danielson, 2021; Simonson, Earl, and Frary, 2021; Simonson, Frary, and Earl, 2023). The intent is to help the instructor think critically about their teaching and look for evidence of effective teaching. Beyond completing the prompts provided in this framework, there are additional tools that will aid reflection including, but not limited to, journaling, various modes of student feedback, peer feedback, student work analysis, recording teaching, and others.  In addition, teaching reflection can be supported and enhanced through collaboration and dialogue with peers because, while no one has the same experience, there are enough similarities and parallels with others to make sharing more likely to result in the discovery of common threads that can lead to critical insights and actions (Brookfield, 1998). 

Use of the FATE-aligned tool 

The FATE reflection tool (Appendix) consists of seven writing exercises and four plans for improvement.  It is not intended that it all be completed in one sitting.  Distributing it across time may actually prove more useful.  An instructor might start with the first two writing exercises to explore what they think they do well and need to improve upon.  The next four writing exercises include personal assessments of the various aspects of teaching, reflections about those assessments from both the student and personal impacts, and then an improvement plan for those aspects of teaching.  The final writing exercise is an overall summary and plan for continuing the journey as a reflective teacher.  In other words, the first six writing exercises focus on teaching and the last on reflection. 

Over the past two years, this framework has been used at six workshops.  Because this has been a reflective process and participants may have been uncomfortable sharing their responses, limited data was collected from participants.  They did indicate that they gained new knowledge and/or skills they can use.  Participants also indicated that they enjoyed the reflection process and found it valuable to pause and think about their teaching and student learning.  Also appreciated were the perspectives and guidance on ways to reflect and improve teaching.  Participants indicated that completing the four tables helped them realize that there were many aspects of teaching they had not previously considered.  In addition, this helped participants learn about best practices and begin to think about how to teach and communicate differently. 

Summary 

Reflective teaching is examining one’s beliefs about teaching and learning and determining the alignment of those beliefs with course planning, classroom implementation, and post-teaching course modification.  The goal is to think critically about one’s teaching to find evidence of effective teaching as well as identifying potential areas for improvement. Effective and reflective educators systematically gather, document, and assess all occurrences during a lesson, transitioning from mere experience to comprehension. This process aids in recognizing and pinpointing areas for improvement, ultimately leading to improved learning outcomes. Thus, to move forward and develop as a reflective teacher, you can: 

• Get into the habit of reflecting on your work
• Think about when you readily reflect and when you avoid reflection
• Identify what you are good at and what you can improve upon
• Collect evidence that supports this
• Familiarize yourself with the evaluative criteria
• Structure your process across the evaluation period
• Make the most of professional development
• Target opportunities that will best meet your needs
• Show what you have learned
• Keep your portfolio up to date

Download the Appendix: The FATE Reflection Tool

---

Dr. Shawn Simonson is a professor and the director of the Human Performance Laboratory in the Department of Kinesiology at Boise State University.  Professional certifications include the Senior Fellow from Advance Higher Education, exercise physiologist – certified from the American College of Sports Medicine, certified strength and conditioning specialist from the National Strength and Conditioning Association, POGIL facilitator from The POGIL Project, TBL trainer-consultant from the Team-Based Learning Collaborative, and master scuba diver trainer from the Professional Association of Dive Instructors.  Simonson conducts research in exercise and environmental physiology as well as in the scholarship of teaching and learning.  He is currently focused on the assessment of teaching (Framework for Assessing Teaching Effectiveness, FATE) at the university level. 

Dr. Megan Frary is a senior educational development consultant in the Center for Teaching and Learning at Boise State University and also clinical associate professor in the Micron School of Materials Science and Engineering at Boise State. Frary’s recent scholarly work has been focused on assessing teaching effectiveness and helping graduate students develop stronger professional identities. She is a Senior Fellow of Advance HE. 

Brittnee Earl is a Boise State graduate earning a BS in psychology and a masters in business administration. She has worked in the Center for Teaching and Learning at Boise State University for nearly a decade as a project manager and more recently as a program coordinator. She has provided support and oversight for several National Science Foundation grants administered through the CTL and also contributes to institutional initiatives focused on improving undergraduate education.

References 

Brookfield, Stephen. 1998. “Critically reflective practice.” Journal of Continuing Education in the Health Professions 18 (4): 197-205. 

Danielson, Charlotte. 2021. The Framework for Teaching Intellectual Engagement: Companion Document – Self-Assessment and Reflection. Chicago, IL: The Danielson Group. 

Kolb, David A. 1993. “The process of experiential learning.” In Culture and Process of Adult Learning, edited by M Thorpe, R Edwards and A Hanson, 138-156. London: Routledge. 

Leon-Henri, Dana Di Pardo. 2020. “Nurturing reflection and networking: The reflective teaching journal.” CONTACT Magazine Spring: 5-13. http://contact.teslontario.org/nurturing-reflection-and-networking-the-reflective-teaching-journal/. 

Merriam-Webster, Inc. 2018. The Merriam-Webster Dictionary. In The Merriam-Webster Dictionary. Springfield, MA: Merriam-Webster, Inc. 

Palmer, Parker J. 2017. The Courage to Teach: Exploring the Inner Landscape of a Teacher’s Life. 20 ed. San Francisco, CA: Jossey-Bass. 

“Reflective Teaching.” 2021. Feedback on Teaching. Yale, Poorvu Center for Teaching and Learning. Accessed November 15. https://poorvucenter.yale.edu/ReflectiveTeaching. 

Simonson, Shawn R, Brittnee Earl, and Megan Frary. 2021. “Establishing a framework for assessing teaching effectiveness.” College Teaching 69: 164-180. https://doi.org/10.1080/87567555.2021.1909528. 

Simonson, Shawn R, Megan Frary, and Brittnee Earl. 2023. “Using a framework to assessing teaching effectiveness (FATE) to promote instructor development and growth.” New Directions for Teaching and Learning 2023 (173): 9-22. https://doi.org/10.1002/tl.20530. 

Von Glaserfeld, Ernst. 1982. “An interpretation of Piaget’s constructivism.” Revue Internationale de Philosophie 36 (142/143): 612-635. https://www.jstor.org/stable/23945415

The post Teaching Excellence Through Mindful Reflection  appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/teaching-and-learning/teaching-excellence-through-mindful-reflection/

Building Community, Collaborative, and Cognitive Classroom Culture

For decades, researchers have highlighted the importance of comprehending and integrating diverse cultural elements to enhance teaching and learning practices. When people hear the term “culture,” it is often associated solely with ethnic culture. However, ethnic culture goes beyond identity and significantly shapes the learning process. The ACCCE model is a framework for applying culturally responsive teaching practices for meaningful learning outcomes (Plotts, 2022). It’s an acronym for five essential cultural aspects: Academic, Collaborative, Cognitive, Community, and Ethnic and Intersectional Culture. These components are necessary to create a thriving educational environment encouraging learners’ growth and accomplishments.  

Culture is the lens through which individuals perceive and make sense of their surroundings, influencing human development and cognition. Culture is also part of human development and influences cognitive, social, and psychological aspects of human development. Recognizing the role of ethnic culture in classroom success is crucial for creating meaningful learning experiences (Thompson, Kirby, & Smith, 2016). Culture is not just about identity; it’s about understanding how culture shapes one’s psychological experiences associated with community, collaboration, and cognition (Plotts, 2022). By acknowledging the impact of culture on community dynamics, collaborative efforts, and cognitive processes, educators can establish a more inclusive and effective learning environment. Most importantly, culture goes beyond the ethnic lens, encompassing community, collaborative, and cognitive cultures. 

Community culture 

Community culture within a classroom comprises the shared norms, values, and structures that influence how students and educators establish connections and build relationships. It represents the collective identity and ambiance that shapes interactions and overall dynamics in the classroom community. Additionally, community culture involves notions of connectedness and exchanges within the group, encompassing concepts such as belongingness and inclusion. In the classroom context, shared norms and values refer to the commonly accepted standards of behavior and the core principles that guide the actions of both students and educators. The community culture contributes to forming a collective identity, a sense of “us” that transcends individual differences. A sense of community is a shared understanding of the purpose of education, the importance of mutual respect, and the pursuit of common learning goals. This collective identity fosters a sense of unity and belonging among classroom community members. Community culture in a classroom is a powerful force that can shape the overall learning experience. It influences how individuals relate to one another, the group engagement level, and the overall sense of community. Fostering a positive and inclusive community culture is essential for creating an environment where students feel empowered to learn, contribute, and thrive. 

Tips for building community culture: 

• In conjunction with their students, instructors can identify shared values about the learning community’s mission and what they hope to experience within the course 
• Develop and utilize community rubrics 
• Provide examples or ideas from past students for building the rubric 
• Define social identities within the learning community (e.g., stakeholders, citizens, decision-makers) 
• Co-create a community-based rubric with your students and co-assess the community bi-weeky 
• Create a space to share communal learning resources by modeling this for your students and asking other faculty members to share their resources with you in the course 

Building collaborative culture 

Numerous students approach collaborative learning experiences with apprehension due to negative past encounters (Capdeferro & Romero, 2012). One of the primary reasons behind this hesitation is the lack of thoughtful consideration given to the culture intended for collaboration. Often, collaborative experiences are assigned without careful regard for the collaborative culture they aim to cultivate. Achieving meaningful collaborative experiences demands specific considerations that are frequently disregarded. Collaborative culture revolves around the norms, values, and mindset associated with collaborative learning experiences. Often overlooked are norms related to group dynamics, power sharing, and a clear understanding of what constitutes meaningful individual contributions to the group. Furthermore, introducing students to small group dynamics for the first time mirrors the first day of class. The dynamics undergo significant changes, particularly if students haven’t had an opportunity to socialize with one another before the start of the collaborative experience. 

Tips for building collaborative culture: 

• Treat the first day of collaborative learning as a new beginning 
• Create a mini-syllabus for collaborative experiences, and leave blank spaces for students to cultivate their own values, norms, and group identity 
• Assist students in establishing values and norms regarding power sharing and meaningful contributions 

Developing cognitive culture 

Culture shapes cognition and human development (Ji & Yap, 2016; Thompson et al., 2016). Cognitive culture pertains to the values, norms, and attitudes regarding the types of thinking that are cultivated and valued in a classroom setting. A considerable portion of the literature dedicated to teaching and learning emphasizes and values the concept of critical thinking. Consequently, critical thinking emerges as one of the predominant and highly prized forms of thinking in academic circles. Nevertheless, it is important to recognize that divergent thinking holds equal value and utility at various points in a course. Faculty members are encouraged to deliberate on the specific types of thinking they wish to emphasize or appreciate and explore additional approaches to thinking that can enhance the overall course experience. Here are various modes of thinking to take into account when constructing assignments, offering inquiry opportunities for students, or revamping an online course: 

• Critical thinking: Evaluating, analyzing, and synthesizing information to form reasoned judgments and make informed decisions (Golden, 2023) 
• Creative thinking: Generating innovative ideas, solutions, and approaches by thinking outside conventional boundaries (Karunarathne & Calma, 2023) 
• Strategic thinking: Planning and executing actions with a long-term perspective, considering various factors and potential outcomes (Commander, 2003) 
• Holistic thinking: Considering the interconnectedness and interdependence of various elements within a system or context (Johnson, 2023) 
• Divergent thinking: Generating various possible solutions or ideas in response to an open-ended question or problem (Fletcher & Benveniste, 2022) 
• Convergent thinking: Focusing on finding a single, correct solution to a well-defined problem (Shettar & Tewari, 2020) 
• Reflective thinking: Examining and analyzing one’s own thoughts, actions, and experiences for personal and professional growth (Chen, Hwang, & Chang, 2019) 
• Systems thinking: Understanding complex systems by examining their components, interactions, and feedback loops (Shaked & Schekter, 2019) 
• Metacognition: Thinking about one’s own thinking processes, understanding how to learn, and managing cognitive resources effectively 
• Emotional intelligence: Understanding and managing one’s own emotions and those of others to navigate social interactions effectively (Khassawneh, Mohammad, Ben-Abdallah, & Alabidi, 2022; Zhoc, King, Chung, & Chen, 2020) 
• Conceptual thinking: Grasping abstract concepts and understanding the relationships between them (Maclellan, 2005) 

Tips for building cognitive culture: 

• Teach students about the different types of thinking that would be most beneficial in the subject matter or teaching style 

• Integrate different types of thinking into the syllabus value statement 
• Guide students in identifying the most effective thinking for different assignments 
• Encourage fanciful thinking before engaging in fact-based or critical thinking activities 
• Differentiate assignments based on different types of thought, but have the same learning goals, objectives, and outcomes 

Final thoughts 

Culture molds learning experiences (Thompson et al., 2016), and culturally responsive teaching is a powerful tool for creating robust learning environments (Byrd, 2016). As faculty members, it is essential for us to broaden our perspective on the impact of culture within our classrooms. Faculty should strive to understand and incorporate cultural applications in their teaching, going beyond traditional notions of culture. This involves intentional consideration of the culture cultivated around the community, collaboration, and cognition in each course, contributing to a more inclusive and purposeful learning environment. This involves a deliberate effort to comprehend how each course can be culturally responsive, extending beyond traditional notions of culture to include considerations of community, collaboration, and cognition. By doing so, we contribute to creating a richer, more inclusive educational atmosphere. 

---

Courtney Plotts, PhD, is an author and speaker, and former national chair of CASEPS. She is also the founder of Neuroculture.   

References 

Byrd, C. M. (2016). Does Culturally Relevant teaching work? An examination from student perspectives. Student Diversity (1), 1-10. https://doi.org/10.1177/2158244016660744 

Capdeferro, N. & Romero, M. (2012). Are Online Learners Frustrated with Collaborative Learning Experiences? International Review of Research in Open and Distributed Learning, 13(2), 26–44. https://doi.org/10.19173/irrodl.v13i2.1127 

Chen, M.-R. A., Hwang, G.-J., & Chang, Y.-Y. (2019). A reflective thinking-promoting approach to enhancing graduate students’ flipped learning engagement, participation behaviors, reflective thinking and project learning outcomes. British Journal of Educational Technology, 50(5), 2288-2307. https://bera-journals.onlinelibrary.wiley.com/doi/10.1111/bjet.12823

Commander, N. E. (2003). A Model for Strategic Thinking and Learning. About Campus, 8(2), 23-25. https://doi.org/10.1177/108648220300800205 

Golden, B. (2023). Enabling critical thinking development in higher education through the use of a structured planning tool. Irish Educational Studies 42(4), 949-969. https://doi.org/10.1080/03323315.2023.2258497 

Fletcher, A., & Benveniste, M. (2022). A new method for training creativity: narrative as an alternative to divergent thinking. Annals of the New York Academy of Sciences, 1512(1), 29–45. https://doi.org/10.1111/nyas.14763 

Johnson, A. (2023). Holistic Learning Theory: More than a Philosophy. Journal of Contemplative and Holistic Education, 1(2), https://doi.org/10.25035/jche.01.02.03.  

Khassawneh, O., Mohammad, T., Ben-Abdallah, R., & Alabidi, S. (2022). The Relationship between Emotional Intelligence and Educators’ Performance in Higher Education Sector. Behavioral Sciences,12(12), 511. https://doi.org/10.3390/bs12120511 

Ji, L. J., & Yap, S. (2016). Culture and cognition. Current Opinion in Psychology, 8, 105-111. https://doi.org/10.1016/j.copsyc.2015.10.001 R. (2023, May 26). “The Power of Education: Unlocking a Brighter Future.” Medium.  

Karunarathne, W., & Calma, A. (2023). Assessing creative thinking skills in higher education: deficits and improvements. Studies in Higher Education, 49(1), 157-177. https://doi.org/10.1080/03075079.2023.2225532 

Maclellan, E. (2005). Conceptual Learning: The Priority for Higher Education. British Journal of Educational Studies, 53(2), 129-147. https://www.tandfonline.com/doi/abs/10.1111/j.1467-8527.2005.00289.x 

Shaked, H., & Sheckter, C. (2019). Systems thinking for principals of learning-focused schools. Journal of School Administration Research and Development, 4(1), 18-22.Retrived from JSARD Full Summer Issue 2019.pdf (ed.gov). 

Shettar, A., M, V., & Tewari, P. (2020). Categorizing student as a Convergent and Divergent Thinker in Problem-solving using Learning Analytics Framework. Procedia Computer Science, 172, 3-8. 

Thompson, B., Kirby, S., & Smith, K. (2016). Culture shapes the evolution of cognition. Proceedings of the National Academy of Sciences, 113(16), 4530-4535. https://doi.org/10.1073/pnas.1523631113 

Zhoc, K. C. H., King, R. B., Chung, T. S. H., & Chen, J. (2020). Emotionally Intelligent Students Are More Engaged and Successful: Examining the Role of Emotional Intelligence in Higher Education. European Journal of Psychology of Education, 35(4), 839-863. 

The post Building Community, Collaborative, and Cognitive Classroom Culture  appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/equality-inclusion-and-diversity/building-community-collaborative-and-cognitive-classroom-culture/

Learning to Surf: Supporting a Campus’s AI Needs

Many colleges and universities have struggled to prepare for generative AI on campus, for instance, by providing guiding policies or pedagogical support. Centralized responses can be helpful but they are typically slow and expensive. To fill immediate gaps, smaller academic programs, such as Critical Thinking Initiatives and Centers for Teaching and Learning, can help campus communities begin engaging with generative AI thoughtfully while fostering student success and workplace readiness.   

To tame their anxieties about AI, faculty and administrators might embrace Howard Kabat-Zinn’s maxim, “You can’t stop the waves, but you can learn to surf.”  It’s time to get in the water. 

Three camps 

On most campuses, faculty fall into three camps:  those who want to “lock and block” AI (just stay out of the water!), those who encourage students to use AI freely in their writing processes (open-ocean swimmers), and, finally, those who want to embrace AI with guardrails (learning to surf). Open-ocean swimmers have argued that their strategy might equalize the playing field for students or mimic workplace writing processes. But experimenting with generative AI (GAI) teaches us that this casual approach might work for experts, but that it might rob students of the critical thinking skills granted by the writing process. Such a practice might also convince administrations that certain departments are unnecessary. At the other end of the spectrum, “lock and block-ers” have banned students’ GAI use altogether. Besides denying students the critical AI skills they may need in the workplace, this approach has often relied upon AI chatbot detectors, which have been proven unreliable and biased (Liang et al., 2023).  

Discord between these three camps, combined with slow university governance procedures, could force the AI waves to a Himalayan height. What can be done?    

Surfing lessons:  Integrating GAI support into an academic program 

I’ve led the Writing Across the Curriculum (WAC) program at CSUF—a large HSI, public land-grant university in Orange County, CA—since 2017. An experience that, when combined with teaching composition and serving as an academic senator, has informed my fathoming of the AI tides approaching higher education’s shores.   

What follows is a case study that can be adapted by a wide range of academic programs, such as faculty development centers, university learning centers, and writing centers. 

Testing the water:  AI boot camps 

As a low-stakes, first step, programs can offer AI-familiarizing experiences during summer or winter breaks.  At CSUF, the WAC program facilitated a summer “ChatGPT/LLM Boot Camp,” which delivered an accessible, open enrollment “GAI Faculty Resources” Canvas site to the campus.  Representatives from CSUF’s eight colleges, the DEI committee, our Instructional Designers team, our Office of Institutional Effectiveness and Assessment, and our Writing Center built the site together while testing the powers and limitations of the Large Language Models (LLMs) that power AI chatbots.  Faculty were paid a small stipend for their participation. Featuring general and college-specific annotated bibliographies, teaching resources, and syllabi guidance, among other things, the site has been consulted by over 500 CSUF faculty, staff, and administrators. 

With a stipend and cross-campus representation, other academic programs can support AI literacy on campus with similar immersive, community-building experiences. 

Riding the first wave:  Proposing AI-infused academic programs 

A boot camp is a solid start, but colleges need more expansive outreach to buoy faculty whose anxiety and burnout on many campuses are palpable. Faculty need empathetic support as they adapt to the technologies encroaching upon their familiar pedagogies. To support them, I proposed connecting writing and AI pedagogies in a new “WAC LIAISONS” program. 

As a writing program administrator, I often deploy “Design Thinking” in my problem solving, which borrows liberally from rhetorical theory. As disciplinary experts, we sometimes rush into the first solution that our expertise suggests to us. Design Thinking (DT) reminds us instead to begin with audience analysis: the first step in DT is to consider your “users’” needs (Raz 2018).  

Directors crafting proposals for new AI-infused programs must first consider their students’ needs, their faculty’s’ needs, and their institution’s needs. “User” needs relevant to CSUF’s WAC LIAISONS program break down into three categories, which exist at many campuses: 

1. Research-informed GAI policies 
2. Professional development and community building for adapting to AI in the classroom 
3. Assessment of student and faculty AI applications 

Next, leaders can propose activities that meet users’ needs while also satisfying their own program’s outcomes.  For our LIAISONS program, these activities included:   

• Need #1: Advising university senate committees as they draft campus AI-use policies.  
• Need #2: 
  • Offering professional development workshops on interrogating and integrating AI in the classroom, including a series on developing AI-informed writing intensive courses.  
  • Facilitating a WAC LIAISONS Faculty Learning Community (FLC) who, besides liaising for their colleges, will produce model writing intensive syllabi with suggested AI policies as well as activities that invite students to engage critically with AI.     
  • Facilitating an annual summer GAI Boot Camp which will respond to future technologies, including opportunities and limitations.   
• Need #3: Assessing the impact of faculty and student use of AI. 

Performing a needs analysis will help program directors identify suitable strategies for specific campus communities and departments.  Directors might, for instance, facilitate an FLC dedicated to updating general education learning goals or design a workshop series for developing AI literacy in tandem with critical thinking skills.     

Budgeting: New program proposals must request funds to stipend members of intensive faculty professional development projects. Directors can expand their program’s outreach by collaborating with other units. For instance, deans may pay additional faculty members’ stipends or support a community-building “AI Café,” at which faculty can celebrate or critique the steps along their AI-ready transitions. Program directors should propose appropriate salary increases or rank changes as well, because this work adds rapid updating of currency in GAI’s developments to directors’ established duties.   

Scanning the horizon:  Assessing AI-supportive programs 

In 2024, I will continue teaching faculty and students the value of “writing to learn” even as we explore how AI might impact that important cognitive process. In addition, I will support faculty as they design authentic assessments that incorporate AI. Universities must assess AI use, not just in the academic programs directly addressing it, but also in classrooms.  A simple example of the former would be determining the percentage of faculty who write “AI-ready” syllabi after using a campus’s AI professional development resources.  An example of the latter would consider students’ needs and achievements.  For instance, because ethical communication is a general education learning goal at CSUF, I can partner with our GE Assessment Committee to gauge students’ achievement of this goal before and after faculty integrate responsible AI-use curricula into their classes.   

Sharing our boards 

Many academic programs will benefit from AI-informed retoolings like these. Directors revamping programs should first ask what their “users” need, then study how they might serve those needs while meeting their programs’ performance outcomes. To increase the chances of budgetary support, directors should provide evidence for the campus need and explain how they will assess the impact of their interventions.   

The ways humans write and research are changing, as they did when the internet was introduced. I could tell you how my students and I are currently using AI, but I can’t predict what writing processes will look like in ten years, or even in five. I may not like the changes, but there’s likely no going backwards: Duolingo and Khan Academy customize tutoring for students with AI, and Microsoft’s 365 AI “Copilot” integrates AI into the entire Office suite. In my mind, it is an ethical obligation to prepare every instructor and student to write and learn critically with AI. Linking AI to our academic programs can help campus communities surf the AI waves, rather than founder in them.   

---

Leslie Bruce earned her PhD in English from USC and her BS in Zoology from CSU Long Beach.  She’s taught composition and literature in California State University, Fullerton’s Department of English since 2007. She’s been honored with CSUF’s “Outstanding Lecturer Award” (2022) and has received an NIH grant for interdisciplinary curricular development (2012-15).  In 2017, she inaugurated CSUF’s Writing Across the Curriculum (WAC) Program, which she transformed into the “WAC LIAISONS” program in 2023.  Leslie’s professional development cultivates faculty’s ability to teach with writing and to adapt to AI’s presence in education.

References 

Liang, Weixin, Mert Yüksekgönül, Yining Mao, Eric Q. Wu, and James Zou. 2023. “GPT Detectors Are Biased against Non-Native English Writers.” Patterns 4 (7): 100779. https://doi.org/10.1016/j.patter.2023.100779.  Accessed Jan. 3, 2024. 

Raz, Ariel. 2018. “Get Started with Design Thinking — Stanford d.School.” Stanford d.School. February 7, 2018. https://dschool.stanford.edu/resources/getting-started-with-design-thinking.  Accessed Jan. 3, 2024. 

The post Learning to Surf:  Supporting a Campus’s AI Needs  appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/academic-leadership/learning-to-surf-supporting-a-campuss-ai-needs/

Drawing in Two Hands: Communication Accommodation with Individuals from Different Cultural Backgrounds

Even though the number of international students and employees within US organizations is increasing (Rivas, Burke, and Hale, 2019), intercultural differences, language barriers, and a desire to avoid conflict and/or offensive language continue to be common communication struggles for both American and international individuals (Rivas et al., 2019; Subtirelu et al., 2022). Hoffman & Zhang (2022) explain that many people also avoid intercultural communication because they struggle to simultaneously maintain their culture and respect others’ cultures due to different cultural interpretations/meanings ascribed to verbal and nonverbal communication (e.g., eye contact as aggressive or respectful). When members of different cultural backgrounds interact, they are potentially opposed to each other because of their different expectations/perceptions, creating a clear sense of “us” and “them” (Gallois, Watson, and Giles, 2018). Such communication can be tense and hostile, and it can descend into overt discrimination and misunderstandings. Thus, understanding and negotiating intercultural conflict is imperative to resolving misunderstandings.  

Cultural competency is the management of human interactions across our differences, with results of more appropriate and effective outcomes at the individual, relational, group, and organizational levels (Engseth, 2018). Communication accommodation theory (CAT) and its three key accommodation strategies can be beneficial to overcome those tensions in intercultural communication and help people grow in cultural competency (Hoffman & Zhang, 2022). Convergence refers to individual strategies to adapt to another person’s communication behavior. Divergence is when people emphasize communication differences between themselves and others (Goodwin, 2019). Maintenance means when the communicator is keeping their communication behavior intact. According to Mdletye (2022), the dominant challenge in successful intercultural communication is the unwillingness or refusal to acquire knowledge unfamiliar with the ways of life people have become used to. Therefore, this activity allows students to leave their comfort zone and learn to accommodate different cultural norms/perceptions. By using communication accommodation strategies, students will learn the challenges of communicating across cultures; how to adjust their communication when experiencing resistance; and finally, how to understand different cultural perspectives and thereby increase their willingness to work effectively with people from different cultures.  

The activity

The activity takes a maximum of 45 minutes to complete.  

Preparation and materials needed 

• Before starting the activity, students should receive a 20-30-minute lecture about cultural competency, cultural misunderstandings (language barrier, nonverbal communication), and communication accommodation theory (convergence, divergence, and maintenance).
• The instructor will provide each student with a piece of paper. Students can use their pen, pencil, or colored pencils (based on their creative preference).  

Round 1: Creating My Culture (10 minutes) 

1. First, the instructor will divide the room into two equal groups: students from planet Mars and students from planet Venus.  
2. The instructor will give each student a piece of paper with instructions explaining their planet’s cultural environment and communication style (see Appendices A and B below).  
3. When students are ready, they will draw a picture of their favorite place on their planet, following the instructions mentioned on their instruction paper.  
4. After finishing their drawing, all students will flip over their paper to keep them private.  

Round 2: Maintaining Our Cultures (two to three minutes) 

1. Students from planet Mars will leave everything on their desks and travel empty-handed to planet Venus and find a partner. Students will not talk to each other or share their drawings. 
2. After finding a partner, both students will hold the same pen/pencil in their hands and draw one picture on the blank side of the student’s paper from planet Venus. Students will draw their favorite place on their planet without communicating to one another while strictly maintaining their own planet’s cultural environment per their instructions from the first round.  
3. In this round, students will experience force/resistance as no person will give up their own culture while drawing with their partners. After finishing this round, students will have about 10 minutes to engage in discussion questions with their drawing partners (see Debriefing section). 

Final Round: Accommodating Our Cultures (two to three minutes) 

1. In this round, the instructor will give the students from planet Venus a new sheet of paper. Holding the same pen/pencil, they will again draw their favorite place from their planets.  But this time, they will communicate the strategies that they discussed after Round 2 and apply those strategies in this final drawing. They will begin to communicate together to create something that ideally represents a merging of both cultures. 

Debriefing 

This activity can be beneficial for students on understanding cultural uniqueness and negotiating conflicts/misunderstandings while working with others. For example, in Round 1, students will be comfortable as they maintain their own culture and work individually. In Round 2, however, they start interacting/working across cultural groups. People from both planets face resistance/force as they strictly maintain their own culture and do not communicate with each other while drawing and experiencing resistance, which can be used as a metaphor for conflict. Using the theoretical concepts discussed in the opening lecture, students are prepared to then engage in a discussion using the following guiding questions:  

• What struggles were you facing when drawing with your partners?  
• Give three to four reasons for struggling with your partner (be specific). 
• What strategies from today’s lecture can both of you implement to improve your drawing with a partner from a different planet and stop the resistance you are feeling? Come up with as much as you can.  

Thus, in the final round, both groups are again drawing together, and this time, they are striving for effective communication and utilizing strategies of cultural competency (e.g., negotiation), and accommodating culture (adjusting/compromising/coming to the middle ground) to negotiate resistance/force (conflict) to work effectively. After they finish the final round, students can then engage in another series of discussion questions: 

• How well do you think you accommodated each other in this round? 
• What were the difficulties, if any, this time? 
• Did you feel/experience any power differences while working with people from different cultural backgrounds on a new planet? If so, explain why.  
• How will this activity help you in a real-life situation where you communicate or work with different cultural people outside the class?  

Appraisal 

Students’ enthusiasm for this activity indicates the activity is highly effective in providing them with opportunities to learn more about intercultural communication. This activity can be assessed in two ways: First, this activity can be completed as a singular class activity to engage students in applying cultural competency concepts and strategies. The debriefing discussion allows instructors to gauge students’ main takeaways and understanding of course concepts. Students could also be asked to write a one-minute paper or longer reflection paper about their key takeaways from the activity, such as experiencing and/or overcoming challenges in working with people in real life from different cultural backgrounds both inside and outside of the classroom. 

This activity is designed to give students practice working with people from different cultural backgrounds/beliefs/norms while learning:

1. the complexities/struggles/conflicts of working with different groups of people,
2. the causes of those complexities/struggles/conflicts (different beliefs/ norms/perceptions, etc.),
3. and strategies to mitigate those complexities and accommodate with different cultural people while working (cultural competency, communication accommodation theory).

In essence, we have found this exercise incredibly powerful for our students, many of whom report they enjoyed the activity and learned to become more understanding while working with people from different cultural backgrounds/perceptions. This activity boosts the students’ interest and confidence in communicating with people from different cultures as they learn to implement the concept of cultural competency and communication accommodation theory in practical situations. With increasing global interaction across a variety of institutions, this activity will benefit students by increasing their confidence and interest in having conversations with different cultural groups as they learn about communication strategies and theory through this activity.  

---

Appendix A: Instructions for People on Planet Venus 

The cultural environment and communication style of Venus
You all belong to Planet Venus. You have a different culture, language, and different values. Interestingly, nobody speaks on your planet. The only medium of communication is drawing. You express your feelings and opinion through art. Also, the structure of your planet is quite different. Everything on your planet is in “triangle shape.” The house is in triangle (base of house, roof is in triangle). People look like triangles. Trees, cars, and all other things are in triangle shape.  

Instructions

1. I will ask you to draw your one favorite place on your planet (e.g., coffee house, street, house, school campus, etc.). But you must do it according to your cultural environment (everything is in triangle). You can use colored pencils to make it look more appealing and creative. 
2. Keep your drawing private. 
3. Do not talk to other planet people while you are drawing. 
4. After finishing your drawing, I will put you in a situation (Round 2). In the new situation, you may experience resistance/force based on your communicative choices (Be ready for that!). 

Appendix B: Instructions for People on Planet Mars 

The cultural environment and communication style of Mars
You all belong to Planet Mars. You have a different culture, language, and different values. Interestingly, nobody speaks on your planet. The only medium of communication is drawing. You express your feelings and opinion through art. Also, the structure of your planet is quite different. Everything on your planet is in “circle shape”. The house is in circle (base of house, roof is in circle). People look like circles. Trees, cars, and all other things are in circle shape.  

Instructions

1. I will ask you to draw your one favorite place on your planet (e.g., coffee house, street, house, school campus, etc.). But you must do it according to your cultural environment (everything is in a circle). You can use colored pencils to make it look more appealing and creative.  
2. Keep your drawing private. 
3. Do not talk to other planet people while you are drawing. 
4. After finishing your drawing, I will put you in a situation (round 2). In a new situation, you may experience resistance/force based on your communicative choices (Be ready for that!) 

Appendix C: Drawings of Students in class  

Figure 1: Student’s Drawing from Venus Group (Round 1)

Figure 2: Student’s Drawing from Mars Group (Round 1)

Figure 3: Students’ drawing maintaining their individual cultures (Round 2)

Figure 4: Students’ drawing accommodating each other’s culture (Final Round)

---

Kazi Wahed (PhD student, University of Nebraska-Lincoln) is a doctoral student in interpersonal, family, and health communication. Her research focuses on art-based research, cultural stigma, and its influences on the specific racial/ethnic community people’s mental health experiences. Currently, she is engaged in a research project based on factors that affect U.S international Students’ self-efficacy in mental Health management: identifying the cultural nuances among international Students.

Angela L. Palmer-Wackerly, (PhD, Ohio State University) is an associate professor in the Department of Communication Studies at the University of Nebraska-Lincoln. She specializes in health equity communication and uses mixed methods, arts-based, and community-based participatory research (CBPR) approaches to study identity, support, and decision-making with (a) individuals and families with invisible illness and (b) health in rural communities. 

References 

Engseth, E. (2018). Cultural competency: A framework for equity, diversity, and inclusion in the archival profession in the United States. The American Archivist, 81 (2), 460-482. https://doi.org/10.17723/0360-9081-81.2.460. 

Goodwin, J. M. (2019). Communication Accommodation Theory: Finding the Right Approach. Georgetown University, USA. https://doi.org/10.4018/978-1-5225-4168-4.ch008. 

Gallois, C., Watson, B.M., & Giles, H. (2018). Intergroup communication: identities and effective interactions. Journal of Communication, 68, 309-317. https://doi.org/10.1093/joc/jqx016. 

Hoffman, W. B., & Zhang, Y. B. (2022). Explaining communication adjustment: communication accommodation theory and its utility in intercultural communication. Journal of Intercultural Communication & Interactions Research, 2(1), 75–100. https://doi.org/10.3726/jicir.2022.1.0005. 

Mdletye, Z. (2022), Overcoming barriers to intercultural communication in higher studies. In Usadolo, E. S., & Oparinde, K (Eds), Communication and Interculturality in Higher Education: Unveiling Contextual Barriers. Cambridge scholars publishing. 

Rivas, J., Burke, M., & Hale, K. (2019). Seeking a sense of belonging: social and cultural integration of international students with American college students. Journal of International Students, 9(2), 682–704. https://doi.org/10.32674/jis.v9i2.943. 

Subtirelu, N. C., Lindemann, S., Acheson, K., & Campbell, M.-A. (2022). Sharing communicative responsibility: training US students in cooperative strategies for communicating across linguistic difference. Multilingua, 41(6), 689–716. https://doi.org/10.1515/multi-2021-0013. 

Verkuyten, M., & Yogeeswaran, K. (2020). Cultural diversity and its implications for intergroup relations. Current Opinion in Psychology, 32, 1–5. https://doi.org/10.1016/j.copsyc.2019.06.010. 

The post Drawing in Two Hands: Communication Accommodation with Individuals from Different Cultural Backgrounds  appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/equality-inclusion-and-diversity/drawing-in-two-hands-communication-accommodation-with-individuals-from-different-cultural-backgrounds/

The Lasso Way to Formative Assessment

We fell in love with Ted Lasso for the obvious reasons–it’s heartwarming, smart, peopled by interesting characters, and full of clever dialogue. But we also fell in love because we are educators who are passionate about assessment. Ted, it turns out, is an excellent reminder of the power of what we might call formative assessment. Throughout the series, he guides his players into various experiences requiring personal and collective reflection about their life goals. Not only does the formula make for some emotional character arcs, but it also serves as an important reminder for all educators, namely, that assessment can be transformational. 

Unfortunately, assessment is too often a euphemism for “accountability.” The goal, it seems, is to ensure that we are doing what we say we are doing. Furthermore, accreditation bodies are looking at assessment to ensure colleges and universities are “living up to what they advertise.” For example, consider a faculty member who pursues assessment for the strict purpose of “satisfying the Dean.” This faculty member may give exams and may collect student artifacts, such as projects or papers, but the faculty really doesn’t connect student performance with the course design or classroom experience. In this scenario, the faculty might be more preoccupied with the question, “Am I doing my job?” than the question, “Are students learning in the best possible way?” 

Assessment as accountability is a boring account of education, and one in which students and faculty members are adversaries who are both just trying to check a box. It’s similar to a team that has lost its way. The players simply do what they are supposed to do without purposeful practice. The stark reality is that more often than not, folks who engage in assessment are doing so to ensure compliance. 

For us, assessment is so much more. It is how we help students recognize where they are and how far they have come. And, it’s not as much about “product” as it is about “process.” The show, Ted Lasso, serves as a good metaphor for this. In many ways, Ted is an expert assessor. He helps his players achieve success as humans. He wants them to grow. He wants them to discover who they are. He wants them to become “the best versions of themselves,” aspirations that are analogized through Ted’s on-the-field strategy: total football. Total football requires all the players to understand one another’s positions and ambitions, creating a synergy in which everyone is interdependent on one another. Through continuous assessment–of self and others–players adapt to any situation to help support one another. In the final season of the show, Trent Crimm, the author documenting the team’s Cinderella story, has this exchange with Ted. 

Trent Crimm: Ted. It’s going to work. 
Ted: Great. What is? 
Trent Crimm: Total football. 
Ted: Okay. Why? 
Trent Crimm: And I’ll tell you why. The Lasso way. You haven’t switched tactics in a week. 
Ted: I haven’t? 
Trent Crimm: No. You’ve done this over three seasons. 
Ted: I have? 
Trent Crimm: Yes. By slowly but surely building a club-wide culture of trust and support through thousands of imperceptible moments, all leading to their inevitable conclusion. Total football. 
Ted: Well, how about that. 

Total assessment

Formative assessment, by definition, is designed to provide both students and instructors with evidence that helps them understand how to proceed as they move through learning content. In a more rigorous explanation, Peggy Maki talks about “real-time assessment” which is designed to be done frequently, with very low stakes, so students and faculty alike can help understand how to move forward (or not) in content.  

Rather than treating assessment as endemic to grades or any other static category, assessment should prioritize movement. Susan Brookhart defines a fundamental aspect of formative assessment as the action towards identified goals. In many ways, this definition extends Vygotsky’s concept of movement between zones of proximal development. For both Brookhart and Vygotsky, action is often driven by feedback. In my (JT) first-year writing courses, for instance, students work to synthesize texts in order to create new conclusions not represented in any single text. Rather than simply correcting students when they struggle with the high-level task of synthesis, I try to provide feedback as an open-ended conversation, asking them questions about their strategies as well as about their understanding of the texts. In my modest attempts to evoke the spirit of Ted Lasso, these interactions often require a sensitivity to who my students are and where they are trying to go in life. In other words, a standardized approach won’t always work. To dive deeper into my approach, just as Ted provided books to his players that represented their life journeys–A Wrinkle in Time to help Roy Kent learn leadership or The Beautiful and the Damned to help Jamie Tartt learn modesty–I often suggest new texts that help illuminate possible pathways that students might take; in other words, my feedback might actually assign more homework in ways that make student projects easier to complete. Or, I might follow recent recommendations in educational research to provide multiple opportunities for students to engage with my feedback, create a revision plan, and try again to meet the project’s objectives. 

In short, rather than collecting data at one particular point of learning and calling it a day, I am always trying to find ways to cycle the data back into the learning experience so that students can develop metacognitive and self-regulatory strategies, employing assessment for their personal and professional growth.  

It was never about Ted 

One of the most inspiring epiphanies on the show comes when Ted reviews Trent Crimm’s draft of the book he wrote about the team. Initially entitled “The Lasso Way,” Ted leaves a note that reads: One small suggestion: change the title. It’s not about me. It never was. 

To create the sense that the courses we teach are about our students–and not about us–we intentionally tap into situational interest. Situational interest occurs when students become engaged in a particular learning situation due to the environmental factors cultivated by course design elements. One of the most reliable ways to create situational interest is to invite student choice. When students make decisions about what or how they learn, they are more likely to take ownership of the experience and exhibit higher levels of engagement. Of course, inviting student choice requires trust. Not only do I have to believe in my students’ capability to make appropriate decisions about research topics, questions, or texts they would like to incorporate into their projects, but they also have to trust that I will not judge or evaluate them based entirely on their decisions. Sure, I will certainly provide feedback guiding their ability to critically evaluate a text if they want to use a blog or questionable website, but even that approach relies on open-ended conversation (e.g., What indicates that this particular source is credible or valid?). Cultivating trust when it comes to student choice means sharing agency in the learning process, which relies on collective participation in assessment. 

During one particular total football practice, Ted assigns each player the name of another player. The goal is for the player to become the other, developing empathy and awareness of how each person fits into the team. When Jamie Tartt, the player who spends the majority of the series thinking about himself and his own development, realizes he’s been assigned himself, he approaches Ted, suggesting a mistake has been made. Ted responds, “We just figured you’d wanna keep doing what you do best for us. Playing striker and scoring goals, right?” 

Jamie, who by now had become situationally interested in “the Lasso way,” is bothered by the suggestion. Rather than correcting Jamie, Ted continuously provides opportunities for Jamie to become reflective and make the best decisions about his play on the team. This example illustrates the patience required to realize the power of formative assessment; it illuminates data about student learning that, through reflective decision making, can be used to improve performance. 

Conclusion 

Teaching is relational. It depends on trust, vulnerability, and openness. Assessment is no different. Done right, assessment elevates all students in advancement towards clearly stated goals. Assessment is often messy in that it usually works differently for different people, whether based on time, task, or performance outcome; but with a little bit of patience and belief, assessment creates a supportive culture that allows students to try new experiences, reflect on the data of the experience, and modify action in constant relational movement. 

---

Chris Hakala is the director of the Center for Excellence in Teaching, Learning, and Scholarship at Springfield College. JT Torres is the director of the Center for Teaching and Learning at Quinnipiac University 

References

Ajjawi, R., Kent, F., Broadbent, J., Tai, J. H. M., Bearman, M., & Boud, D. (2022). Feedback that works: a realist review of feedback interventions for written tasks. Studies in Higher Education, 47(7), 1343-1356.

Brown, G. T., Peterson, E. R., & Yao, E. S. (2016). Student conceptions of feedback: Impact on self‐regulation, self‐efficacy, and academic achievement. British Journal of Educational Psychology, 86(4), 606-629.

Cogliano, M., Bernacki, M. L., & Kardash, C. M. (2021). A metacognitive retrieval practice intervention to improve undergraduates’ monitoring and control processes and use of performance feedback for classroom learning. Journal of Educational Psychology, 113(7), 1421-1440.

Nagro, S. A., Fraser, D. W., & Hooks, S. D. (2019). Lesson planning with engagement in mind: Proactive classroom management strategies for curriculum instruction. Intervention in School and Clinic, 54(3), 131-140.

Schraw, G., Flowerday, T., & Lehman, S. (2001). Increasing situational interest in the classroom. Educational Psychology Review, 13, 211-224.

Torres, J. T. (2022). Feedback as Open-Ended Conversation: Inviting Students to Coregulate and Metacognitively Reflect during Assessment. Journal of the Scholarship of Teaching and Learning, 22(1), 81-94.

The post The Lasso Way to Formative Assessment  appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/educational-assessment/the-lasso-way-to-formative-assessment/

AI-Oh My! A Closer Look at AI Tools for Educators

Many of you have probably tinkered with Artificial Intelligence (AI) applications and programs, or perhaps you are advanced in your journey of AI tools and could teach us a few things about how you are using AI in the classroom. (Don’t hesitate to use the chat section at the bottom of this article to share more tips, tricks, and resources that we can all use!) But for those of you who are hoping for a list of AI resources, a little encouragement, and a brief explanation of what’s out there, look no further. As your Faculty Focus editor, I did a little digging, investigating, and exploring to see what some of these programs could do. You may not find them all beneficial to your classes or daily life, but perhaps there are a few tools you find resourceful.

Perplexity

http://perplexity.ai/

Pricing: A free plan is available.

What can it do? Perplexity is similar to other AI chat services but it also lists the sources in which its answers come from. For instance, I asked, “What are the best wellbeing strategies I can implement for the new year?” The image below shows: the generated sources (all clickable with a direct link), the answer to your question, and other related prompts or questions.

QuestionWell

https://www.questionwell.org

Pricing: A free plan is available along with other monthly paid plans that include additional features.

What can it do? QuestionWell allows you to input an article, reading, or a video and writes questions based on what you’ve input and your learning outcomes. You can:

• Add a topic so the AI knows what your overall goal is of the article
• Add learning outcomes or standards (optional)
• Change the language
• Change the reading level
• Select the question type you would like generated (multiple choice, fill-in-the-blank, short answer)

As an example, I took a Faculty Focus article and created a topic, one learning outcome, selected the multiple-choice question type, set my reading level to graduate, and copy and pasted the article into the prompt box. The image below shows both the essential questions and multiple-choice questions that were generated. You can also export the questions you have chosen and integrate them into a quizzing system or LMS such as Canvas, Quizziz, Kahoot, Blackboard, and more.

Curipod

https://curipod.com/

Pricing: A free plan is available along with other monthly paid plans that include additional features.

What can it do? Curipod can generate an interactive slide deck (nine to 12 slides) in seconds on any topic. It can also integrate polls, word clouds, brain breaks, drawing prompts, and more. You can add and edit any of the slides. In addition to full slideshow lessons, Curipod has interactive activities such as co-writing a fairy tale with AI, getting feedback from a historical figure, a “convince the evil AI ruler” prompt, brain breaks, and more!

Adobe Firefly

https://firefly.adobe.com/

Pricing: A free plan is available along with other monthly paid plans that include additional features.

What can it do? Adobe Firefly uses generative AI and text prompts to create images that match exactly what you are looking for. You can thumbs up or thumbs down each image to let the AI know what you like and don’t like. You can also select different effects you want integrated to make your images exactly how you want them.

Pictory.ai

https://pictory.ai/

Pricing: They offer a free trial plan that allows you to create three, free video projects, along with a paid monthly and yearly plan.

What can it do? Pictory can automatically convert podcast recordings, webinar recordings, blogs, and more into video snippets for posting on social media. It can also automatically add captions to your videos and turn blog posts into videos with SEO keywords.

Eduaide.ai

www.eduaide.ai

Pricing: They offer a free trial plan that allows you to create three, free video projects, along with a paid monthly and yearly plan.

What can it do? Eduaide.ai is an AI-powered teaching assistant designed to help teachers with lesson planning, instructional design, and generating educational content. It offers a resource generator, teaching assistant, feedback bot, and AI chat.

Canva Classroom Magic

https://www.canva.com/education/

Pricing: They offer a free edu account for teachers with canva.com/education

What can it do? Canva Classroom Magic has multiple AI tools to utilize for your classroom.
Magic Write: Create a prompt or general first draft, reword it with Magic Write for specific learning goals or to better summarize the text. You can also adapt it to specific reading levels.
Magic Animate: Automatically animate your designs with a click. Students can also create their own animations or use it for class presentations.
Magic Grab: Quickly extract or modify text in documents or screenshots.
Magic Switch: Reformat your class assignments, projects, and more. Turn your ideas into ready-to-use presentations.
Alt Text Suggestions: Text suggestions will instantly generate captions or tags for images and videos to add accessibility.

Other AI resources:

• https://ditchthattextbook.com/ai-tools/
• https://www.bu.edu/cds-faculty/culture-community/gaia-policy/
• https://www.edutopia.org/article/7-ai-tools-that-help-teachers-work-more-efficiently

The post AI-Oh My! A Closer Look at AI Tools for Educators appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/teaching-with-technology-articles/ai-oh-my-a-closer-look-at-ai-tools-for-educators/

Human or AI? Connectives Hold the Clues

The introduction of mass market writing tools powered by Artificial Intelligence (AI) has changed higher education. Proponents of AI claim that AI tools should be integrated into lesson design, however, it is also the case that AI may be used by students as an unethical shortcut to wholly complete written assignments. While companies such as GPTZero have responded to academic concerns by creating software designed to detect the use of AI in written work, false positives and underconfidence in the software’s assessment leaves instructors without an actionable means to promote integrity in coursework (Chaka, 2023). Independent of software applications, there may be other signals that distinguish independent student work from that of AI. Gibbs (2023) conducted a review involving 1.2 million words generated by ChatGPT (a commonly used AI tool) and concluded that, when compared to a human writer, it is roughly 1,000 times more likely to use the term “re-imagined,” 400 times more likely to use the term “graphene,” and more than 600 times likely to use the term “bioluminescent.”  This approach suggests the value of a similar comparison: to identify terminology that is uniquely human; that is, terms that are largely absent from material that are produced by AI. Such terms may be found within the arena of connective terminology.  

Literature review 

Writing assignments have traditionally served as a means to support the development of critical thinking skills in higher education. Although AI tools are positioned to replace many of the processes involved in completing writing assignments, universities have embraced the tools as a potential means to redefine critical thinking and writing projects, calling on students to evaluate the quality of AI responses. Of course, one may prompt an AI tool to evaluate its own responses, so ensuring that students themselves conduct the evaluations remains an important endeavor in higher education. 

Connectives are a large group of terms inclusive of conjunctions (such as and), prepositions (such as before), and adverbs (such as however). There is a precedent for using such terms as a means to distinguish the backgrounds of language users, often as a means to differentiate between native speakers (NS) and non-native speakers (NNS) of a language. In a comparison of student English essays by NS and NNS of French origin, Granger and Tyson (1996) found that NNS were far less likely to use a term such as “instead” in their writing. At the same time, the researchers found that NNS used a term such as “indeed” at nearly four times the frequency of NS. Ma and Wang (2016) compared essays written in English by British and American students to essays written in English by Cantonese students. In the study, researchers noted many similarities in connective usage, but also noted that NS used the term “because” with higher frequency. Kuswoyo et al. (2020) compared language usage in NS and NNS of English among engineering lecturers. The researchers found that the NNS tended to use “and” and “so” more frequently than NS in lectures.  

Beyond connectives, usage of other parts of language have also been leveraged as a means to identify differences in writers’ origins.  Zhao (2017) compared language use in four groups: NS and NNS graduate students as well as NS and NNS English scholars.  While the author found many similarities among students in terms of connective use, there was a notable difference in the use of logical, grammatical metaphors (using terms such as “factors” to express a causal relationship) when comparing student work to that of scholars.  

The literatures’ findings suggest that the use of connectives provides a means to distinguish NS from NNS. Of course, AI writing tools are neither NS nor NNS.  AI writing tools are more properly classified as Large Language Models (LLMs). Unlike humans, LLMs generate text based on probabilities. Unlike humans, LLMs do not (presumably) have beliefs or sensory information beyond prompts. Given that both LLMs and humans use language, however, an investigation of term frequency may also provide a means for distinguishing whether written text has been generated by a humans or by AI.  

Methods 

Given the body of research suggesting that the frequency of terms used may provide information about its author’s identity, a project was launched to determine whether such terms, specifically connectives, might provide objective grounds for differentiating AI writing from that of a student. With permission of the institutional review board (the “Research Institute”), 34,170 words generated by 49 students in response to writing prompts in general education courses at a single-purpose institution were compiled into a single document. The same prompts were submitted to two widely available and free artificial intelligence writing tools, ChatGPT and Bing, in January of 2024. The process yielded 9,503 words generated by the AI tools.  

The prompts given to both students and AI were as follows: 

• Identify a myth about the populations studied (including older adults and economically disadvantaged). Integrating a citation and a reference, dispel the myth. 
• Identify two subprovisions within the American Nurse Association’s ethical code that might conflict with each other. Explain the potential conflict and a potential resolution. 
• Describe and assess a hypothetical event using moral theories studied (egoism, determinism, Kant’s Categorical Imperative, consequentialism, and relativism).  

To generate 9,503 words from the AI tools, additional prompts such as “A different response please” were issued after receiving its initial response to the identified prompts.  Use of common connectives by students and AI were tabulated, respectively, by leveraging the Find tool (CMD+F) within document software.  

Results 

The results of the study are depicted in Table 1.  Calculating frequency of observed instances per 1,000 words provides a venue for comparing connective use in student and AI writing.  Based on frequency of occurrence, there was little difference in the use of terms such as “again” or “and.”  

However, AI was three times more likely to use the term “however” than a student. Conversely, students were five times more likely to use “if,” fifteen times more likely to use “because,” and ten times more likely to use the term “so” in their writing.  Notably, the terms “since” and “too” did not appear in AI writing, but were found 14 and 27 times (respectively) in student writing.  

Term	Collective Student Responses    (word count: 34,170)		Collective AI Responses   (word count: 9,501)
	Observed Instances	Frequency per 1,000 words	Observed Instances	Frequency per 1,000 words
again	25	0.73	8	0.84
also	90	2.63	16	1.68
and	1,067	31.23	384	40.42
because	129	3.78	2	0.21
but	112	3.28	8	0.84
however	37	1.08	33	3.47
if	358	10.48	19	2.00
since	14	0.41	0	0.00
so	63	1.84	1	0.11
then	24	0.79	1	0.11
too	27	0.79	0	0.00

Table 1: Frequency of Connectives in Student and AI Writing 

Given initial observed differences between student and AI written material, additional terms were searched with a focus on experiences that were unique to conscious beings, such as “think,” “want,” and “believe(s).” Table 2 depicts the results. In particular, students were 17 times more likely than AI to use the term “think.”  In a happy accident, a typographical error related to “think” revealed an additional difference in terminology: within student work, the term “thing” was used 109 times. The term occurred only one time in AI work. The term, inclusive of extensions such as “nothing” and “anything,” is 30 times more frequently found in student writing.  

Term	Collective Student Responses    (word count: 34,170)		Collective AI  Responses    (word count: 9,501)
	Observed Instances	Frequency per 1,000 words	Observed Instances	Frequency per 1,000 words
appear(s)	9	0.26	1	0.11
believe(s)	38	1.11	4	0.42
feel(s)	48	1.40	4	0.42
seem(s)	15	4.32	5	0.53
think(s)	66	1.93	1	0.11
want	46	1.35	4	0.42

Table 2: Frequency of Consciousness-Based Terms in Student and AI Writing 

Conclusions 

AI software will continue to evolve. Users may direct the tool to leverage terms associated with human writers such as “think” and “so”, and the resulting AI-generated text would perhaps obscure the differences in language usage as observed in this project.  Further, the absence of terminology associated with student writing does not impart certainty that a written text has been composed by AI. The results of this project do not provide an indubitable foundation to address academic integrity concerns.  

However, the findings of this study do suggest some concrete, measurable differences between student writing and that of AI. Armed with such knowledge, instructors may review student work with a better understanding of features that might suggest reliance on AI that is outside the boundaries of integrity.  The study provides measurements that may add depth and understanding to existing hunches and suspicions when reading AI-generated text.  Such an understanding provides a better starting point for any potential intervention.  

---

Miriam Bowers Abbott, MA, is an associate professor at Mount Carmel College of nursing in Columbus, Ohio. She teaches courses on ethics and culture and serves as assistant director in the online RN to BSN program.

Wyatt Abbott is a student at Kansas State University where he studies psychology and communication.

References 

Chaka, C. (2023). Detecting AI content in responses generated by ChatGPT, YouChat, and ChatSonic. The case of five AI content detection tools. Journal of Applied Learning & Teaching 6(2).  https://journals.sfu.ca/jalt/index.php/jalt/article/view/861 

Gibbs, J. (2023). Which words does ChatGPT use most? Medium. https://medium.com/@jordan_gibbs 

Granger, S. and Tyson, S. (1996). Connector usage in English essay writing of native and non-native EFL speakers of English. World Englishes 15(1). https://www.researchgate.net/publication/227647492_Connector_Usage_in_the_English_Essay_Writing_of_Native_and_Non-Native_EFL_Speakers_of_English 

Kuswoyo, H., Sujatna, E. T. , Indrayani, L.M. , & Rido, A. (2020). Cohesive conjunctions and and so as discourse strategies in English native and non-native engineering lecturers: A corpus-based study. International Journals of Advanced Science and Technology 29(7) https://www.researchgate.net/profile/Heri-Kuswoyo-2/publication/344486791_Cohesive_Conjunctions_and_and_so_as_Discourse_Strategies_in_English_Native_and_Non-Native_Engineering_Lecturers_A_Corpus-Based_Study/links/5f7bef34a6fdccfd7b4a7b1d/Cohesive-Conjunctions-and-and-so-as-Discourse-Strategies-in-English-Native-and-Non-Native-Engineering-Lecturers-A-Corpus-Based-Study.pdf 

Ma, Y., and Wang, B. (2016) A corpus-based study of connectors in student writing: A comparison between a native speaker (NS) corpus and a non-native speaker (NNS) learner corpus. International Journal of Applied Linguistics 5(1). https://journals.aiac.org.au/index.php/IJALEL/article/view/1968 

Zhao, J. (2017). Native speaker advantage in academic writing? Conjunctive realizations in EAP writing by four groups of writers. Ampersand (4).https://www.sciencedirect.com/science/article/pii/S2215039016300650 

The post Human or AI? Connectives Hold the Clues  appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/teaching-with-technology-articles/human-or-ai-connectives-hold-the-clues/

Ghost Students: The Rise of Bots in Online Education

Artificial intelligence (AI) has led to the development of sophisticated conversational systems known as chatbots. These AI-powered programs can provide information, answer questions, and even complete tasks. Chatbots are increasingly common in customer service, healthcare, and education; however, in education, chatbots have been used to generate false or misleading information called “hallucinations” and create fake students.  

Chatbot hallucinations in higher education are caused by the complex nature of educational queries and the diverse range of topics encountered. Community college chatbots need to understand a wide range of academic subjects, courses, and student queries. This is different from generic applications where chatbots may only handle customer service inquiries. 

Ambiguity in educational queries  

Students often ask complex and context-specific questions about course requirements, program details, and academic pathways. The inherent ambiguity in these queries can challenge chatbots, leading to misinterpretations and, subsequently, hallucinated responses. For instance, a student inquiring about the prerequisites for a specific course may provide incomplete information, triggering a chatbot hallucination if the system fails to infer the intended meaning accurately. 

• Data bias and inconsistencies: The reliance on educational databases and resources for chatbot training data introduces the risk of bias and outdated information. Inaccuracies in the training data, whether reflecting biased perspectives or containing outdated facts, can contribute to the generation of hallucinated responses. Chatbots must navigate a vast array of academic subjects, making it crucial to address bias and ensure the accuracy of information embedded in their knowledge base. 
• Human-chatbot interaction dynamics: The unique dynamics of human-chatbot interactions further complicate the issue of hallucinations. College settings foster collaborative learning environments, where students engage in dynamic discussions and group activities. Chatbots operating in such settings must navigate the complexities of ambiguous queries arising from collaborative interactions, increasing the risk of misinterpretations and subsequent hallucinations. Additionally, feedback loops in educational contexts where students inadvertently provide incorrect information during interactions with chatbots can reinforce inaccurate patterns and perpetuate hallucinations in subsequent interactions. 

Implications of chatbot hallucinations in higher education 

The implications of chatbot hallucinations extend beyond the general concerns seen in broader applications. In the educational domain where precision and reliability are paramount, the consequences of misleading information can significantly impact students’ academic journeys. 

• Academic performance: Misleading information related to course prerequisites or curriculum details can have tangible effects on students’ academic performance. If a chatbot provides inaccurate details about the requirements for a specific course, students may enroll without the necessary preparation, potentially leading to suboptimal academic outcomes. 
• Career guidance: Hallucinated responses regarding career advice or program recommendations can misguide students, influencing their educational and professional trajectories. Inaccurate guidance may lead students to pursue paths that are not aligned with their interests or long-term goals, hindering their overall development. 
• Application processes: Chatbots often assist students with inquiries about application procedures, deadlines, and required documentation. Inaccurate information in these critical areas can result in students missing opportunities or facing unnecessary challenges during the enrollment process. The potential for confusion and frustration among students underscores the importance of mitigating hallucinations in these specific contexts. 

Growing problems and motives behind bots posing as students 

In higher education there is a troubling trend: the use of bots to register as students, particularly in online classes. This may sound far-fetched but it is a reality that colleges and universities are facing today. The motive behind the use of bots is to defraud colleges and universities. By registering for classes without any intention of attending, these bots can inflate enrollment numbers, leading to financial losses for institutions, and universities are still responsible for paying faculty members for the classes even if the seats are filled with bots. 

These automated programs are being used for various reasons, ranging from gaining access to popular classes to scamming institutions out of money.  According to Tytunovich (2023) in California, over 65,000 fake applications for financial aid were submitted in the state’s community college system in 2021, with one community college identifying and blocking approximately $1.7 million in attempted student aid fraud. The San Diego Community College District was not so lucky and paid out over $100,000 in fraudulent claims before catching on.  According to the Chancellor’s Office, about 20% of the traffic coming to the system’s online application portal is from bots and other “malicious” actors (West et al., 2021). 

Feature	Bots	Chatbots
Primary function	Automate tasks	Communicate and provide information
User interaction	No direct user interaction	Direct user interaction through natural language
Typical use cases	Customer service, marketing, social media	Customer service, education, e-commerce

Figure 1. “Bots vs Chatbots” gives examples of each

Potential use and misuse by students

In the article “OpenAI’s Custom Chatbots Are Leaking Their Secrets,” the author discusses how OpenAI’s GPTs give individuals the ability to create custom bots. A more recent development is the creation of custom bots by users. Open AI subscription holders can now create custom bots also known as AI agents. These versatile tools can be tailored for personal use or shared publicly on the web.   

The positive use would include the transformation of the online learning experience for students by offering personalized learning support, enhancing engagement and interaction, providing real-time feedback, assisting with study preparation, and offering language support. Despite the potential benefits in classroom settings, their use also raises concerns. These include over-reliance, plagiarism, bias, limited creativity, ethical considerations, accessibility issues, oversimplification, distraction, and dehumanization of the learning experience. 

Utilizing CAPTCHA responses to differentiate humans from bots  

CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is a widely employed tool for distinguishing between human users and automated programs. By presenting challenges that are straightforward for humans to solve but difficult for bots to overcome, CAPTCHAs can effectively filter out bots and protect online platforms from malicious activity (Stec, 2023).  

Common CAPTCHA types 

There are various types of CAPTCHAs, each with their strengths and limitations. Some common CAPTCHA types include: 

• Text-based CAPTCHAs: These CAPTCHAs display a series of distorted letters or numbers that are difficult for bots to read but easy for humans to decipher. For instance, a CAPTCHA might present a sequence of distorted letters like “594nB” and ask the user to type it out correctly. 
• Image-based CAPTCHAs: These CAPTCHAs present a grid of images and ask the user to identify specific objects in the images. For instance, a user might be asked to select all the images containing traffic lights or all the images featuring cats. Image-based CAPTCHAs are particularly useful for individuals with visual impairments as they can utilize audio CAPTCHAs as an alternative. 
• Audio-based CAPTCHAs: These CAPTCHAs play a recording of spoken words or numbers and ask the user to type what they hear. This type of CAPTCHA is particularly useful for individuals with visual impairments who may struggle with text-based or image-based CAPTCHAs. 

Examples of CAPTCHA challenges 

Specific examples of CAPTCHA challenges that can be used to distinguish between humans and bots include: 

• Distorted text CAPTCHA: The user is presented with a sequence of distorted letters or numbers and asked to correctly type them out. The distortion makes it difficult for bots to accurately identify the characters while humans can easily read them. 
• Object recognition CAPTCHA: The user is shown a grid of images and asked to select all the images containing a specific object, such as cats, traffic lights, or mountains. This challenge relies on human visual perception which bots often struggle with. 
• Audio CAPTCHA: The user is played a recording of spoken words or numbers and asked to type out what they hear. This challenge tests the user’s ability to understand and transcribe spoken language, a task that is difficult for bots. 
• Tile Sorting CAPTCHA: The user is presented with a set of scrambled tiles and asked to arrange the tiles to form a complete image. This challenge requires spatial reasoning and pattern recognition skills which are not well-developed in bots. 

By employing CAPTCHAs in various forms, online platforms can effectively distinguish between genuine human users and automated programs, safeguarding the integrity of their services and protecting against malicious activities.

Figure 2. “What is CAPTCHA and what are its different Types?

Additional considerations for CAPTCHA implementation 

While CAPTCHAs are an effective tool for distinguishing between humans and bots, it is important to consider their potential impact on user experience. CAPTCHAs that are too difficult or time-consuming can frustrate users and lead to increased abandonment rates. Additionally, CAPTCHAs should be designed to be accessible to individuals with disabilities, such as those with visual or auditory impairments. 

Overall, CAPTCHAs can play a crucial role in protecting online platforms from automated attacks and ensuring that they are used by genuine human users. By carefully selecting and implementing appropriate CAPTCHA challenges, online platforms can balance security with user experience and maintain a safe and reliable environment for all users. 

Combating bot misuse in higher education 

Faculty can play a crucial role in mitigating the misuse of bots in higher education by implementing proactive measures and fostering a culture of academic integrity. Key strategies include: 

• Educating students: Dedicate class time to discuss the impact of bots, outline course policies, and organize workshops on academic integrity. 
• Implementing technology-based detection: Collaborate with IT to integrate CAPTCHA challenges and plagiarism detection software. Establish clear reporting procedures for suspected bot usage. 
• Designing effective assessments: Emphasize critical thinking, incorporate open-ended questions, and utilize a variety of assessment methods. Implement authenticity checks for online submissions.   
• Proactive monitoring: Regularly review online discussions, encourage student engagement, and collaborate with teaching assistants to identify potential bot activity. 
• Fostering open communication: Maintain an open-door policy, promote peer support, collaborate with colleagues, and participate in institutional initiatives focused on academic integrity. 
• Verification processes: Implement additional verification processes during registration such as requiring a valid student ID or a video introduction. This can make it more difficult for bots to register as students. 
• Reporting mechanism: Establish a reporting mechanism where faculty and students can report suspected bot activity. This can help in early detection and prevention of bot-related fraud. 
• Policy development: Develop and enforce strict policies against the use of bots in online classes. This could include penalties for students found to be using bots. 

By implementing these comprehensive measures, faculty can effectively address the growing challenge of bots and safeguard academic integrity for all students.  Remember, the goal is to maintain the integrity of the educational experience for all students. By taking these steps, faculty can help address the issue of bots posing as students and ensure a fair and equitable learning environment. 

---

Dave E. Balch, PhD, is a professor at Rio Hondo College and has published articles in the areas of ethics, humor, and distance education. Balch has been awarded excellence in teaching by the Universities of Redlands and La Verne, and has also been awarded  “Realizing Shared Dreams: Teamwork in the Southern California Community Colleges” by  Rio Hondo College.

Note: This article was the result of a collaboration between the human author and two AI programs; Bard and Bing. 

References 

Burgess, M. (2023, November 29). OpenAI’s custom chatbots are leaking their secrets. Wired. https://www.wired.com/story/openai-custom-chatbots-gpts-prompt-injection-attacks/

Google. (2023, March). Google. https://bard.google.com/  

Metz, C. (2023, November 6). Chatbots May ‘Hallucinate’ More Often Than Many Realize. The New York Times. Retrieved from https://www.nytimes.com/2023/11/06/technology/chatbots-hallucination-rates.html

Microsoft. (2023, February). Bing. https://www.bing.com/searchform=MY02AA&OCID=MY02AA&pl=launch&q=Bing%2BAI&showconv=1  

Stec, A. (2023, May 5). What is CAPTCHA and how does it work?. Baeldung on Computer Science. https://www.baeldung.com/cs/captcha-intro  

Tytunovich, G. (2023, October 5). Council post: How Higher Education became the target of bots, fake accounts and online fraud. Forbes. https://www.forbes.com/sites/forbestechcouncil/2023/01/20/how-higher-education-became-the-target-of-bots-fake-accounts-and-online-fraud/?sh=34246b781f62  

West, C., Zinshteyn, M., Reagan, M., & Hall, E. (2021, September 2). That student in your community college class could be a bot. CalMatters. https://calmatters.org/education/higher-education/college-beat/2021/09/california-community-colleges-financial-aid-scam/  

The post Ghost Students: The Rise of Bots in Online Education  appeared first on Faculty Focus | Higher Ed Teaching & Learning.

from Faculty Focus | Higher Ed Teaching & Learning https://s39613.pcdn.co/articles/teaching-with-technology-articles/ghost-students-the-rise-of-bots-in-online-education/