A guide supporting faculty in designing assignments and learning experiences that preserve critical thinking, creativity, and integrity in an era of generative AI.
This guide supports faculty in designing assignments and learning experiences that preserve critical thinking, creativity, and integrity in an era of generative AI.
Table of Contents & Navigation Aids
This section provides a sample table of contents and suggested navigation aids for the Faculty Guide. Given the length of the document and the 100 included activities, clear structure is essential to usability. Faculty should be able to quickly find relevant sections and activities.
Introduction
AI Risk Rubric
Sample Assessment Rubrics
Accessibility & UDL Addendum
Privacy & Ethics Note
Discipline-Specific Inserts
100 Faculty Activities by Domain
References
Pilot & Evaluation Plan
- **Domain Labels**: Each activity should include a tag for its domain (Cognitive, Creative, Metacognitive, Social/Ethical, Information/Integrity).\ - **AI Risk Icons or Labels**: Each activity should clearly indicate its AI risk level (Low, Partial, High). Use text labels rather than emojis for accessibility.\ - **Design Fix Notes**: Activities in the High-risk category should include a design fix suggestion immediately after the description.\ - **Assignments & Assessments**: Where included, these should be clearly labeled in a consistent format.\ - **Generative AI Brainstorm Prompts**: Faculty-facing prompts should be highlighted at the end of activity descriptions, under a consistent heading.
- In the Word version: Use **Heading styles** so faculty can use the navigation pane.\ - In the PDF version: Include clickable bookmarks for major sections.\ - In the LMS version: Break activities into modular pages or folders by domain.\ - Consider adding a one-page \'How to Use This Guide\' overview at the start.
Introduction
In *Exercised* (Lieberman, 2020), evolutionary biologist Daniel Lieberman shows that physical exercise, once built into daily survival tasks, now must be engineered into our lives through gyms, sports, and routines. The same is becoming true for mental exertion in the age of artificial intelligence.\ \ Where once students had to summarize, restate, or draft ideas as essential steps in learning, tools like generative AI now automate many of those functions. Faculty rightly fear a process of deskilling---that students will lose the opportunity to practice critical thinking, creativity, empathy, and judgment if learning is reduced to outsourcing tasks to machines. As MIT's *Your Brain on ChatGPT* report (2023) highlights, heavy reliance on generative AI can shift cognitive load away from these core skills.\ \ This guide begins from the premise that, just as physical fitness now requires intentional exercise, intellectual fitness now requires intentional learning design. Faculty must engineer environments that exercise students' thinking \'muscles\' across five domains:
Critical thinking, problem framing, decision-making, and transfer of learning.
Creativity, flexibility, curiosity, and resilience in the face of challenges.
Reflection, self-regulation, judgment of learning, and learning agility.
Collaboration, communication, perspective-taking, and civic reasoning.
Information literacy, source evaluation, digital integrity, and misinformation awareness.
This guide provides 100 practical activities across these domains. For each, we identify the level of AI risk, provide design fixes, suggest assignments and assessments, and include optional faculty-facing generative AI prompts for brainstorming.\ \ The goal is not to avoid AI entirely but to design learning experiences where students still do the intellectual heavy lifting. Like exercise, these skills must be practiced deliberately, repeatedly, and authentically if they are to endure.
AI Risk Rubric for Learning Activities
This rubric helps faculty categorize assignments and activities based on their vulnerability to being completed primarily by AI tools. The goal is to guide design decisions that ensure students are practicing the intended skills, not outsourcing them. Risk levels apply to tasks, not to students.
Risk Level Indicators Examples Design Priority
Low Requires live In-class Focus on
interaction, debate, authentic
embodied practice, reflective engagement and
or personal journal, lab transparent
experience. with unique criteria.
Involves unique data, improv
context/data not warm-up.
in AI training
sets. Student
thinking is
visible (oral,
iterative,
collaborative).
Partial Some elements can Case study Add scaffolds
be AI-assisted analysis, that highlight
(summarizing, concept reasoning and
organizing, mapping, process, not
drafting), but literature just final
core learning review matrix, product.
outcomes still prototype
require student design.
judgment, context,
or collaboration.
AI can accelerate
but not replace
the task.
High Task can be fully Restating Redesign tasks
or mostly problems, to surface
automated with AI paraphrasing process
without articles, (multiple
demonstrating first-draft drafts, oral
intended learning. summaries, defense,
Product-oriented simple reflection).
with minimal comparative
process critiques.
visibility.
- This rubric applies to activities and assignments --- not to students.\ - A single assignment can shift categories depending on how it's structured (e.g., \'compare two articles\' is High risk if written only, but Partial if students must present and defend orally).\ - Faculty should consider pairing High-risk tasks with Design Fixes to recover the intended skill practice.
Sample Assessment Rubric: Case Study Analysis (Critical Thinking)
This sample rubric provides faculty with clear criteria for assessing student performance in a case study analysis. It focuses on critical thinking, reasoning, and evidence use --- skills that can be partially AI-assisted but must ultimately be demonstrated by the student.
Criteria Beginning Developing Proficient Advanced
Problem Problem is Problem is Problem is Problem is Identification vague, identified but clearly precisely misidentified, incomplete or identified with articulated with or missing. lacks clarity. some context rich context and provided. significance.
Use of Evidence Little or no Some evidence Relevant Evidence is evidence; provided but evidence is comprehensive, evidence is weakly used well-chosen, and irrelevant or integrated or appropriately integrated with incorrect. partially to support strong relevant. reasoning. reasoning.
Analysis & Analysis is Some reasoning Sound reasoning Sophisticated Reasoning superficial, is evident, with logical reasoning; descriptive but analysis analysis of multiple only, or is incomplete main issues. perspectives and illogical. or partially complexities flawed. explored.
Recognition of No recognition Acknowledges Considers Thoroughly Trade-Offs of alternative alternatives trade-offs and evaluates viewpoints or but with alternatives trade-offs and trade-offs. limited with reasonable integrates them explanation. explanation. into final conclusions.
Communication & Writing or Some Clear, Exceptional Organization presentation is organization organized clarity, unclear, but with communication organization, disorganized, or lapses in with logical and engagement difficult to clarity or flow. in follow. flow. communication.
- This rubric can be adapted for written, oral, or group case study assignments.\ - Faculty may assign point values to each level (e.g., 1--4) to generate a total score.\ - Transparency: Share the rubric with students in advance to guide their preparation.\ - AI Risk Consideration: To reduce AI overuse, require students to annotate reasoning steps or present orally.
Sample Assessment Rubric: Fact-Checking Assignment (Information & Integrity Skills)
This sample rubric supports faculty in assessing a fact-checking assignment. The focus is on students' ability to evaluate information, document their evidence trail, and reflect on challenges in verifying claims.
Criteria Beginning Developing Proficient Advanced
Evidence Trail Little or no Some sources Complete Comprehensive, documentation of documented but evidence trail transparent sources; evidence incomplete or showing evidence trail missing or inconsistently relevant, with annotations irrelevant. cited. credible explaining source sources. choices.
Accuracy of Verification is Some claims Most claims All claims Verification incorrect or verified accurately verified absent; claims correctly, but verified with accurately with remain errors or gaps credible triangulated, unsubstantiated. remain. sources. high-quality sources.
Source No evaluation of Some evaluation Credibility of Sophisticated Evaluation credibility; of credibility sources evaluation of sources used but superficial evaluated with source uncritically. or incomplete. relevant credibility with criteria (e.g., clear author, bias, justification. accuracy).
Reflection on No reflection or Some reflection Thoughtful Deep, critical Challenges minimal comments on difficulties reflection on reflection on on the process. but lacks depth verification verification or specificity. challenges and challenges, how they were strategies, and addressed. lessons for future practice.
Communication & Work is unclear, Some Clear, Exceptionally Clarity poorly structured, organization, organized clear, engaging, or difficult to but lapses in presentation of and follow. clarity or fact-checking well-structured coherence. process. communication of findings.
- This rubric can be applied to written reports, presentations, or digital portfolios.\ - Faculty may assign point values (e.g., 1--4) to generate a score for each criterion.\ - Transparency: Share with students to clarify expectations of thorough verification and integrity.\ - AI Risk Consideration: Require students to document process steps (screenshots, annotations) that AI cannot replicate.
Accessibility & Universal Design for Learning (UDL) Addendum
This addendum ensures that all activities and assignments in the Faculty Guide are inclusive and equitable. Not all students can participate in live debates, service-learning, or fieldwork in the same way. Universal Design for Learning (UDL) principles help provide multiple means of engagement, representation, and expression so that all learners can demonstrate the intended skills.
- **Multiple Means of Engagement**: Offer options for live, asynchronous, and online participation.\ - **Multiple Means of Representation**: Provide materials in accessible formats (captioned videos, screen-reader-friendly docs, alt-text for images).\ - **Multiple Means of Expression**: Allow students to demonstrate skills in different formats (written, oral, multimedia).
- **Barrier**: Live debates may exclude students with speech, hearing, or anxiety-related disabilities.\ - **Alternative**: Allow asynchronous video or written debates, with peers responding over time.\ - **UDL Note**: Assess reasoning and evidence use, not speed or performance style.
- **Barrier**: Not all students can travel off-campus or engage in community placements.\ - **Alternative**: Offer virtual service-learning or campus-based engagement projects.\ - **UDL Note**: Assess civic reasoning and reflection rather than physical presence.
- **Barrier**: Embodied, live role-play may exclude students with mobility or processing differences.\ - **Alternative**: Allow simulation-based or text-based role-play using online platforms.\ - **UDL Note**: Assess adaptability and perspective-taking, not performance delivery.
- **Barrier**: Some students cannot travel or safely access certain field sites.\ - **Alternative**: Use publicly available datasets, virtual labs, or simulations.\ - **UDL Note**: Assess data literacy and analysis rather than physical data collection.
- **Barrier**: Live presentations may disadvantage students with speech or hearing disabilities.\ - **Alternative**: Allow pre-recorded videos, audio presentations, or accessible slide decks with transcripts.\ - **UDL Note**: Assess clarity, organization, and reasoning, not delivery style alone.
- Include accessibility statements in syllabi and assignment sheets.\ - Provide clear rubrics that evaluate *skills* rather than format of delivery.\ - Consult with Disability Services and use institutional accessibility checklists.\ - Normalize choice by framing alternatives as equally rigorous, not as accommodations.
Privacy & Ethics Note for Learning Activities
Some assignments in this guide ask students to engage with community members, collect data, or document online activity. These activities raise important considerations related to privacy, ethics, and compliance with laws such as FERPA (U.S.) or GDPR (Europe). Faculty should proactively address these issues to protect students, community partners, and research integrity.
- **Informed Consent**: If students interview or observe others, ensure participants provide informed consent. Faculty should supply sample consent forms and clarify voluntary participation.
- **Anonymization & Redaction**: Student submissions should remove or mask identifying details (names, photos, contact info). Screenshots should be redacted to show only relevant evidence.
- **FERPA Compliance**: Faculty must avoid requiring students to disclose personal educational records (grades, IDs, schedules) in public forums or shared assignments.
- **GDPR & Data Protection**: In courses with international students, faculty must ensure compliance with GDPR principles when handling personal data (minimization, consent, purpose limitation).
- **Use of AI Tools**: When assignments involve AI, clarify what student data may be exposed. Encourage use of institutionally approved tools and prohibit sharing sensitive personal or institutional data with third-party systems.
- Provide students with a brief **Ethics & Privacy Guide** at the start of the course.\ - Require reflective notes on how students addressed privacy/ethics concerns in assignments.\ - For projects involving human participants, seek guidance from Institutional Review Boards (IRB) or equivalent committees.\ - For online or social media projects, focus on analyzing *publicly available* content rather than requiring students to engage in data scraping or surveillance.
Faculty may adapt the following statement for syllabi or assignments:\ \ \"This course values ethical and responsible engagement with information and people. In assignments involving interviews, observations, or online content, you are expected to protect privacy and comply with institutional and legal standards. Do not share personally identifying information in your submissions. When in doubt, consult your instructor for guidance.\"
Discipline-Specific Inserts
While the activities in this guide are broadly applicable, faculty often need to see examples in their own disciplines. The following inserts provide 2--3 sample activities in each domain for four broad areas: STEM, Social Sciences, Arts & Humanities, and Professional Programs. These are meant as adaptable models, not prescriptions.
**Activity: Lab Data Analysis with Local Dataset**\ - AI Risk: Partial\ - Design Fix: Require students to collect or generate original data.\ - Assignment: Students analyze locally generated lab data (not from published datasets) and compare results to theory.\ - Assessment: Accuracy of analysis, quality of reflection on discrepancies.
**Activity: Engineering Ethics Case**\ - AI Risk: Partial\ - Design Fix: Require oral defense of reasoning.\ - Assignment: Students analyze a case of engineering failure and present lessons learned in a short oral defense.\ - Assessment: Depth of ethical reasoning, clarity of oral communication.
**Activity: Community Survey Analysis**\ - AI Risk: Partial\ - Design Fix: Require primary data collection.\ - Assignment: Students design and administer a small survey, then analyze results.\ - Assessment: Quality of data collection, accuracy of analysis, clarity of conclusions.
**Activity: Policy Memo on Local Issue**\ - AI Risk: High\ - Design Fix: Require interviews with local stakeholders.\ - Assignment: Students write a memo on a local social policy issue, integrating interview findings.\ - Assessment: Integration of perspectives, clarity, and feasibility of recommendations.
**Activity: Comparative Literature Analysis**\ - AI Risk: High\ - Design Fix: Require use of non-digitized or archival sources.\ - Assignment: Students compare two works using primary sources available in local archives.\ - Assessment: Depth of comparison, integration of unique materials.
**Activity: Performance or Creative Response**\ - AI Risk: Low\ - Design Fix: Require embodied or performed output.\ - Assignment: Students create a performance, artwork, or creative writing response to a course theme.\ - Assessment: Originality, alignment with theme, clarity of reflection.
**Activity: Clinical Simulation (Health)**\ - AI Risk: Low\ - Design Fix: Require live role-play with feedback.\ - Assignment: Students participate in a simulated patient interview and treatment plan exercise.\ - Assessment: Communication skills, accuracy, professionalism.
**Activity: Business Case Pitch**\ - AI Risk: High\ - Design Fix: Require live Q&A with peers or external judges.\ - Assignment: Students pitch a business solution and respond to audience questions.\ - Assessment: Clarity of pitch, quality of responses, feasibility of solution.
**Activity: Lesson Plan Design (Education)**\ - AI Risk: Partial\ - Design Fix: Require reflection on student needs and context.\ - Assignment: Students design a lesson plan tailored to a specific learner group and justify choices.\ - Assessment: Appropriateness of strategies, evidence of reflection, alignment with objectives.
Domain 1: Core Cognitive Skills
This domain emphasizes reasoning, problem framing, decision-making, and transfer of learning. Activities in this section are designed to help students practice critical thinking and structured judgment, skills that may be partially supported but not replaced by AI. Each activity includes an AI Risk rating, a design fix (if needed), a suggested assignment/assessment, and optional generative AI brainstorming prompts for faculty.
AI Risk: Low
Design Fix: No major fix needed; ensure roles and evidence use are clear.
Assignment/Assessment: Students participate in a timed, structured debate on a course-related question, citing evidence.
Assessment Strategy: Rubric on clarity, evidence use, and reasoning.
Generate a list of debate topics relevant to [discipline].
Suggest scaffolds to help novice students prepare for a debate.
AI Risk: Partial
Design Fix: Require oral defense or annotated reasoning steps to ensure process visibility.
Assignment/Assessment: Students analyze a case study and present a solution in class with justification.
Assessment Strategy: Rubric on problem identification, reasoning, and recognition of trade-offs.
List case study scenarios in [discipline] that require ethical decision-making.
Suggest reflection questions that encourage deeper analysis of a case.
AI Risk: High
Design Fix: Require students to compare conflicting sources and explain credibility judgments.
Assignment/Assessment: Students evaluate multiple sources on the same claim and rank their credibility.
Assessment Strategy: Rubric on criteria for source credibility and justification of rankings.
Provide examples of common misinformation in [discipline].
Suggest questions students could use to test the reliability of a source.
AI Risk: Low
Design Fix: No major fix needed; ensure students verbalize reasoning steps.
Assignment/Assessment: Students solve a problem aloud in small groups, narrating their reasoning.
Assessment Strategy: Instructor checklist of reasoning clarity and accuracy.
Suggest strategies for training students to verbalize their reasoning.
List common reasoning errors in [discipline] students should avoid.
Domain 2: Creative & Adaptive Skills
This domain emphasizes creativity, flexibility, curiosity, and resilience. Activities are designed to help students generate original ideas, adapt to uncertainty, and practice divergent thinking. While AI tools can assist with brainstorming, authentic creativity requires personal expression, context sensitivity, and reflective iteration.
AI Risk: Low
Design Fix: Ensure accessibility alternatives are available for students uncomfortable with live performance.
Assignment/Assessment: Students engage in improvisational role-play to respond to an unexpected scenario related to the course.
Assessment Strategy: Checklist of adaptability, engagement, and relevance to scenario.
Suggest improv scenarios in [discipline] that would stretch adaptability skills.
Generate strategies to assess creativity without bias toward performance style.
AI Risk: Partial
Design Fix: Require a reflective justification of design choices to move beyond surface-level AI outputs.
Assignment/Assessment: Students redesign a product, system, or text for a new audience or purpose.
Assessment Strategy: Rubric on originality, relevance to new context, and clarity of justification.
List redesign challenges suitable for [discipline].
Suggest reflection questions to help students explain their creative process.
AI Risk: Low
Design Fix: Encourage authentic entries by connecting prompts to personal experience.
Assignment/Assessment: Students keep a weekly curiosity journal documenting questions, observations, or puzzles related to course content.
Assessment Strategy: Completion check plus rubric on depth of inquiry and connections made.
Provide journal prompts that spark curiosity in [discipline].
Suggest ways students can connect journal entries to broader course themes.
AI Risk: Partial
Design Fix: Require students to connect reflection to personal growth and future strategies.
Assignment/Assessment: Students analyze a case of failure or challenge (historical or personal) and reflect on resilience strategies.
Assessment Strategy: Rubric on depth of reflection, application of resilience concepts, and clarity of strategies.
List historical or disciplinary cases that highlight resilience in [discipline].
Suggest reflection prompts to help students connect case lessons to their own learning journey.
Domain 3: Metacognitive Skills
This domain emphasizes reflection, self-regulation, judgment of learning, and learning agility. Activities in this section are designed to help students monitor and direct their own thinking and learning processes. While AI can support by providing feedback or generating study aids, authentic metacognition requires students to evaluate their own strategies, progress, and decisions.
AI Risk: Partial
Design Fix: Require students to compare their perceptions with instructor or peer feedback.
Assignment/Assessment: Students keep a weekly learning journal documenting strategies used, successes, and challenges, including a self-rating of progress.
Assessment Strategy: Rubric on depth of reflection, accuracy of self-assessment, and integration of feedback.
Generate reflective journal prompts that encourage metacognition in [discipline].
Suggest ways to help students compare self-assessment with external feedback.
AI Risk: Low
Design Fix: No major fix needed; ensure students reflect on preparation and outcome, not just scores.
Assignment/Assessment: After an exam, students complete a structured reflection (exam wrapper) on preparation strategies, mistakes, and plans for improvement.
Assessment Strategy: Checklist of completion plus rubric on quality of reflection.
List reflection questions students should answer in an exam wrapper.
Suggest ways to connect exam wrapper insights to future study strategies.
AI Risk: Low
Design Fix: Require goals to be measurable and tied to course outcomes.
Assignment/Assessment: Students set specific learning goals at the start of the term and review progress at midterm and end.
Assessment Strategy: Rubric on clarity of goals, evidence of monitoring, and quality of adjustments made.
Generate examples of measurable learning goals in [discipline].
Suggest reflection prompts for midterm goal review discussions.
AI Risk: Partial
Design Fix: Require students to verbalize and critique their study strategies in real time.
Assignment/Assessment: Students record themselves studying a concept while narrating their strategy choices and then reflect on effectiveness.
Assessment Strategy: Rubric on clarity of narration, depth of reflection, and alignment with effective strategies.
List common ineffective study strategies in [discipline].
Generate reflection prompts for students to evaluate the success of their own strategies.
Domain 4: Social & Ethical Skills
This domain emphasizes collaboration, communication, perspective-taking, and civic reasoning. Activities are designed to help students build interpersonal skills, navigate ethical dilemmas, and engage in meaningful dialogue. While AI tools can model communication, authentic learning in this domain requires human interaction and reflection on ethical consequences.
AI Risk: Partial
Design Fix: Require peer evaluation and reflection on team dynamics.
Assignment/Assessment: Students complete a group project addressing a real-world problem, with deliverables and group reflection.
Assessment Strategy: Rubric on teamwork, communication, and quality of deliverable.
Suggest group project topics in [discipline] that require collaboration.
Generate peer evaluation questions to assess contributions fairly.
AI Risk: Low
Design Fix: Ensure diverse perspectives are represented and discussed.
Assignment/Assessment: Students debate an ethical dilemma relevant to the discipline, using evidence and ethical frameworks.
Assessment Strategy: Rubric on clarity of ethical reasoning, respect for opposing views, and evidence use.
List current ethical dilemmas in [discipline] that students could debate.
Generate discussion questions that help students explore multiple perspectives.
AI Risk: Low
Design Fix: Encourage reflection on emotional as well as intellectual insights.
Assignment/Assessment: Students adopt the perspective of a stakeholder in a case and write or present from that viewpoint.
Assessment Strategy: Rubric on accuracy of perspective, empathy, and clarity of expression.
Provide stakeholder scenarios in [discipline] where perspective-taking is key.
Suggest reflection prompts to help students analyze what they learned from role adoption.
AI Risk: Partial
Design Fix: Require reflective documentation of process and learning, not just final output.
Assignment/Assessment: Students engage in a civic engagement activity (e.g., voter registration drive, advocacy campaign) and reflect on their role.
Assessment Strategy: Rubric on civic reasoning, impact of activity, and depth of reflection.
List civic engagement projects that connect to [discipline].
Suggest reflection prompts for connecting civic engagement to course learning outcomes.
Domain 5: Information & Integrity Skills
This domain emphasizes information literacy, source evaluation, digital integrity, and misinformation awareness. Activities are designed to help students critically engage with information, assess credibility, and practice ethical use of sources. While AI tools can generate summaries or suggest sources, authentic skill development requires students to evaluate, cross-check, and reflect on information independently.
AI Risk: High
Design Fix: Require justification of rankings and comparison of multiple perspectives.
Assignment/Assessment: Students review several sources on a current issue and rank them by credibility with explanations.
Assessment Strategy: Rubric on criteria for credibility, justification of rankings, and clarity of reasoning.
List examples of mixed-quality sources in [discipline] for students to rank.
Generate reflection prompts for students to explain how they judged credibility.
AI Risk: Partial
Design Fix: Require annotated evidence trails and reflection on challenges.
Assignment/Assessment: Students fact-check a claim from media or social media and submit a report with documentation.
Assessment Strategy: Rubric on accuracy of verification, completeness of evidence trail, and depth of reflection.
List common misinformation themes in [discipline].
Suggest ways students can triangulate information from multiple sources.
AI Risk: Partial
Design Fix: Require personal reflection on usefulness of sources beyond AI-generated summaries.
Assignment/Assessment: Students compile an annotated bibliography and reflect on how each source contributes to their project.
Assessment Strategy: Rubric on accuracy of citations, quality of annotations, and depth of reflection.
Provide examples of strong annotation language in [discipline].
Suggest reflection prompts for evaluating source usefulness.
AI Risk: Low
Design Fix: Ensure cases are current and connected to real-world digital ethics issues.
Assignment/Assessment: Students analyze a case involving plagiarism, data misuse, or academic integrity and propose solutions.
Assessment Strategy: Rubric on ethical reasoning, proposed solutions, and clarity of communication.
List current digital integrity issues relevant to [discipline].
Generate discussion questions that connect digital ethics to professional practice.
References
The following references provide foundational research and frameworks that support the design of this Faculty Guide. They demonstrate alignment with established scholarship in higher education, assessment, metacognition, information literacy, and teaching in the age of AI.
American Association of Colleges and Universities (AAC&U). (2009). VALUE Rubrics. https://www.aacu.org/value-rubrics
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive--developmental inquiry. American Psychologist, 34(10), 906--911.
Lieberman, D. E. (2020). Exercised: Why Something We Never Evolved to Do Is Healthy and Rewarding. Pantheon.
MIT Media Lab. (2023). Your Brain on ChatGPT: Risks and opportunities of generative AI for cognition. Massachusetts Institute of Technology.
National Research Council. (2012). Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century. National Academies Press.
Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching, and assessing. Theory Into Practice, 41(4), 219--225.
Stanford History Education Group. (2019). Civic Online Reasoning curriculum. https://cor.stanford.edu
Weimer, M. (2013). Learner-Centered Teaching: Five Key Changes to Practice (2nd ed.). Jossey-Bass.
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64--70.
Pilot & Evaluation Plan
To ensure the effectiveness of the Faculty Guide, a structured pilot and evaluation plan should be implemented. This plan provides a roadmap for testing selected activities, gathering data, and refining materials before broader adoption.
- Test a representative set of activities across the five skill domains.\ - Gather faculty and student feedback on clarity, usability, and effectiveness.\ - Identify challenges in implementation (time, resources, accessibility).\ - Assess impact on student engagement and skill development.
- Select 2--3 departments with diverse disciplines (e.g., STEM, Social Sciences, Humanities).\ - Recruit volunteer faculty (5--10) willing to integrate at least two activities.\ - Include a range of course levels (introductory, advanced) to test adaptability.
- **Faculty Surveys & Focus Groups**: Collect feedback on ease of integration, student response, and observed learning outcomes.\ - **Student Feedback Surveys**: Anonymous reflections on which activities helped them think, create, or collaborate.\ - **Rubric-Based Assessment**: Use the sample assessment rubrics to measure student performance.\ - **Learning Artifacts Review**: Analyze a sample of student work products for evidence of skill development.
- At least 75% of faculty report the activities were usable and improved engagement.\ - At least 70% of students report the activities helped them practice thinking or learning skills.\ - Evidence from student work shows growth in targeted skills (as measured by rubrics).\ - Accessibility and UDL adaptations are feasible in practice.
- **Semester 1**: Recruit faculty, select activities, provide orientation.\ - **Semester 2**: Implement pilot, collect midterm and end-of-semester data.\ - **Semester 3**: Analyze results, refine guide, prepare for broader dissemination.
- Share pilot results with faculty senate or teaching and learning center.\ - Revise the guide based on findings.\ - Develop professional development workshops to support adoption.\ - Consider publishing results in a teaching and learning journal for peer validation.