Education Case Study Topics

Strong case studies turn classroom theories into real decisions, policies, and measurable outcomes. As TopicSuggestions, we work with students on research every week, so we know that picking a precise, researchable topic is half the battle. Today we will come up with some ideas for you, and we will keep them practical and ready to use. Our thesis is simple: curated, well-scoped case study topics help you move from vague interests to actionable projects with clear data and methods.

Good Case Study Topic ideas on Education

In this post, we will share a list of topics grouped by K–12, higher education, EdTech, equity and inclusion, assessment, teacher development, policy, and community partnerships, with a one-line angle for each to guide scope and potential evidence.

1. We Build a Carbon-Aware Edge Offloading Orchestrator for Household IoT

– We ask how we can fuse real-time grid carbon intensity, device battery health, and latency constraints to schedule computation across phones, routers, and home gateways.
– We evaluate whether our multi-objective scheduler reduces emissions and energy costs without degrading QoE for AR, gaming, and smart-home workloads.
– We investigate how we can design a resilient “carbon oracle” that validates provider data and handles data gaps via uncertainty-aware decision-making.
– We study how we can communicate trade-offs to households with explainable dashboards that shift behavior without inducing alert fatigue.

2. We Create a Verifiable Reproducibility Ledger for No-Code ML Pipelines Using Verifiable Credentials and WASM Sandboxes

– We examine how we can capture provenance of drag-and-drop ML steps as signed claims that are tamper-evident yet privacy-preserving.
– We test whether sandboxed WASM replays of pipelines can deterministically reproduce results across browsers and operating systems.
– We analyze how we can issue, revoke, and verify contributor credentials to support collaborative audits and course grading at scale.
– We measure how we can minimize overhead while preserving end-to-end verifiability and explainability for non-expert users.

3. We Invent Bioacoustic, Context-Aware CAPTCHAs Optimized for Screen Reader Users

– We explore how we can transform transient ambient soundscapes into solvable, privacy-preserving challenges that exclude bots without relying on vision.
– We evaluate whether adaptive difficulty using user hearing profiles and device microphones improves accessibility and security simultaneously.
– We investigate how we can defend against replay and synthetic audio attacks via on-device liveness cues and room impulse responses.
– We assess how we can meet legal accessibility standards while maintaining acceptable completion times and low cognitive load.

4. We Prototype Mixed-Reality Remote Labs with Predictive Haptic Compensation over Unreliable Networks

– We study how we can forecast force-feedback signals with sequence models to mask jitter and packet loss in student lab activities.
– We test whether calibration-free, commodity haptic devices can approximate high-end rigs through learned perception-alignment.
– We measure how we can balance safety constraints with responsiveness when controlling physical instruments through MR overlays.
– We investigate how we can auto-generate scaffolding hints from telemetry to improve learning outcomes in remote STEM courses.

5. We Engineer a Self-Healing Drone–Ground Mesh Network Guided by Natural-Language Routing Intents

– We ask how we can translate high-level human intents (e.g., “prioritize medical telemetry, avoid no-fly zones”) into safe, optimized routes.
– We evaluate whether intent-to-policy compilers can adapt to topology churn and partial GPS denial while maintaining SLAs.
– We test how we can coordinate drone repositioning to restore connectivity with minimal energy while preventing oscillations.
– We investigate how we can verify safety and fairness properties of intent-driven routing under adversarial interference.

6. We Deploy Edge-Native Digital Twins for Urban Beekeeping with Explainable Anomaly Detection

– We explore how we can fuse hive acoustics, thermal profiles, and weight sensors to predict swarming, disease, and queen loss on-device.
– We evaluate whether interpretable models can provide actionable explanations for interventions that hobbyists can execute.
– We test how we can generalize across microclimates and hive types via transfer learning without leaking precise location data.
– We study how we can quantify ecological co-benefits (pollination proxies) and city heat-island mitigation with twin-to-twin collaboration.

7. We Build Socially Negotiated Consent Agents for Multi-Tenant IoT Rentals with Formal Policy Learning

– We investigate how we can model roommate and landlord preferences as machine-checkable social contracts that resolve IoT data disputes.
– We evaluate whether interactive agents can learn acceptable defaults from prior negotiations while proving compliance via runtime monitors.
– We test how we can enforce contextual integrity across shared cameras, locks, and sensors without centralizing raw data.
– We study how we can design UX that enables rapid, comprehensible renegotiation when occupants or devices change.

8. We Design a Carbon- and Privacy-Aware Recursive Resolver Selector (“Green DNS”)

– We examine how we can jointly optimize DNS resolver choice for latency, carbon intensity of paths, and privacy guarantees.
– We evaluate whether client-side multi-armed bandits with carbon oracles can outperform static DoH/DoT selections in practice.
– We test how we can mitigate resolver and path fingerprinting while maintaining verifiable sustainability claims.
– We analyze how we can standardize resolver attestation for energy and privacy properties without enabling greenwashing.

9. We Develop Privacy-Preserving Occupancy Analytics via On-Device mmWave–Thermal Sensor Fusion Resistant to Adversarial Attacks

– We explore how we can achieve accurate counts and flow estimates without reconstructing identities or body shapes.
– We evaluate whether self-supervised fusion improves robustness to spoofing, occlusions, and environmental drift.
– We test how we can certify differential privacy guarantees while preserving temporal utility for building control.
– We investigate how we can detect and withstand physical and digital adversarial perturbations targeting either modality.

10. We Orchestrate Federated Continual Learning Across Family Device Clusters with Shared Differential Privacy Budgets

– We study how we can allocate privacy budgets across household members and devices to personalize models fairly over time.
– We evaluate whether concept-drift detection can trigger budget reallocation without leaking sensitive usage patterns.
– We test how we can compress and schedule updates under intermittent connectivity and heterogeneous hardware.
– We investigate how we can design consent and transparency flows that explain cross-user benefits and risks in plain language.

11. Teacher interaction with adaptive learning algorithm recommendations

We propose to study how teachers interpret, negotiate, and override adaptive system recommendations.
We ask: How do we interpret algorithm confidence signals when deciding pacing and grouping? We ask: How does the visibility of the model’s uncertainty change our willingness to follow or contest recommendations? We ask: How do iterative teacher corrections reshape algorithm behavior and classroom norms?
We will work on this through mixed methods: we run classroom vignette experiments, collect teacher think‑aloud protocols during live use, analyze LMS logs for override patterns, and co-design explanation prototypes with teachers for A/B testing.

12. Micro‑sabbaticals for early‑career teachers and classroom innovation

We propose evaluating short, funded micro‑sabbaticals as a lever for pedagogical innovation and retention.
We ask: How do we measure changes in instructional practices and risk‑taking after a 2–4 week micro‑sabbatical? We ask: How does participation affect our intent to remain in the profession across three years? We ask: How do we select participants to avoid amplifying inequities?
We will pilot a cluster randomized trial across districts, pair quantitative classroom observation tools with longitudinal retention metrics, and conduct cost‑benefit and equity impact analyses alongside qualitative interviews.

13. Augmented reality place‑based curricula for displaced and refugee youth

We propose designing AR modules that reconstruct local histories and place attachments for recently displaced learners.
We ask: How do we build AR experiences that increase our sense of belonging and place‑knowledge in host communities? We ask: How does co‑created AR content affect engagement and content transfer in social studies? We ask: What ethical safeguards do we need for sensitive cultural content?
We will co‑design with youth and community museums, run iterative field trials in informal learning sites, use pre/post measures of belonging and content mastery, and conduct participatory evaluation with refugees.

14. Haptic‑augmented collaborative note‑taking in high school science labs

We propose investigating wearable haptic cues that scaffold group coordination and spatial reasoning during hands‑on labs.
We ask: How do we integrate haptic feedback into our collaborative note workflows to improve procedural accuracy? We ask: How does haptic scaffolding influence equitable participation among group members? We ask: Does haptic support transfer to offline spatial problem solving?
We will prototype low‑cost haptic wearables, run within‑class randomized group assignments, combine video discourse analysis with lab performance metrics, and iterate device design based on student feedback.

15. The effect of algorithmic grading opacity on student motivation and help‑seeking

We propose to examine how perceived opacity or transparency of automated grading shapes student behavior.
We ask: How do we change study strategies when we believe grading is algorithmic and opaque versus transparent and explainable? We ask: How does perceived opacity affect our propensity to seek help or contest grades? We ask: What explanatory formats reduce harmful gaming of algorithmic assessments?
We will conduct online experiments with manipulated grade explanations, track subsequent study time and help‑seeking, run follow‑up interviews, and test intervention materials that increase perceived procedural fairness.

16. Co‑designing formative assessments with neurodivergent students

We propose partnering with neurodivergent learners to redesign formative assessments that better capture diverse demonstrations of learning.
We ask: How do we collaboratively define valid evidence of learning across neurotypes? We ask: How does co‑design affect our sense of agency and assessment anxiety? We ask: What psychometric trade‑offs emerge when assessments become multimodal by necessity?
We will use participatory action research, iteratively prototype multimodal assessment tasks, perform qualitative usability testing, and conduct psychometric analyses (e.g., generalizability studies) to evaluate reliability and fairness.

17. Curricula addressing climate anxiety and subsequent civic engagement in adolescents

We propose testing curricular framings that balance emotional validation with actionable civic pathways.
We ask: How do we reduce paralyzing anxiety while increasing constructive civic engagement? We ask: Which pedagogical framings (alarm, hope, systems analysis) produce sustained civic behaviors over 12 months? We ask: How do identity and local context moderate these effects?
We will develop three curricular versions, implement a cluster randomized trial in diverse schools, measure psychological outcomes and civic action proxies (e.g., community projects, voter registration drives), and analyze moderating factors.

18. Peer‑mediated learning hubs for students with chronic health conditions

We propose studying peer‑run micro‑learning hubs (virtual and physical) that maintain continuity for students who miss school for health reasons.
We ask: How do we structure peer facilitation to sustain curricular momentum and social connection? We ask: What impact do hubs have on our attendance, grades, and wellbeing? We ask: How do hubs interact with existing special education and health services?
We will establish pilot hubs, train peer facilitators, collect mixed quantitative outcomes (attendance, performance) and qualitative narratives, and model scalability and integration with school supports.

19. Language‑dialect code‑switching policies and conceptual learning in STEM classrooms

We propose exploring explicit teacher policies that allow/restrict code‑switching between home dialects and standard academic registers in STEM instruction.
We ask: How do we negotiate code‑switching to maximize conceptual understanding without stigmatizing home varieties? We ask: What policy variants (free code‑switching, translanguaging scaffolds, explicit register instruction) produce better concept retention? We ask: How do students’ identities and metalinguistic awareness mediate outcomes?
We will design classroom interventions, perform discourse and misconception analyses, use concept inventories with embedded transfer tasks, and conduct teacher professional learning to observe policy enactment.

20. Sensor‑driven adaptive classroom acoustics for attention equity

We propose deploying real‑time acoustic sensors that adapt amplification and reverberation controls to support diverse attention profiles.
We ask: How do we calibrate adaptive acoustics to improve attention and comprehension for neurodiverse students without disrupting others? We ask: What seating‑based or group‑based inequities persist despite acoustic adjustments? We ask: What privacy and consent protocols are required for sensorized classrooms?
We will implement sensor networks in pilot classrooms, run A/B tests with acoustic adjustments, combine behavioral attention measures and learning outcomes, and conduct stakeholder workshops to co‑develop ethical governance.

21. Adaptive microlearning for multilingual refugee students to reduce math anxiety

We ask: RQ1 — How does an adaptive microlearning platform with native-language scaffolds affect math anxiety and short-term achievement among multilingual refugee students? RQ2 — How do learners engage with micro-lessons across language modes and what patterns predict drop-off? RQ3 — How do teachers perceive integration of microlearning into trauma-informed pedagogy? We will conduct a mixed-methods quasi-experimental study with pre/post anxiety and achievement measures, learning-analytics of microlesson interactions, and teacher/student interviews; we will iteratively refine adaptive rules using A/B tests and thematic coding.

22. Augmented reality (AR) field trips to mitigate “place deficit” and build spatial identity in urban youth

We ask: RQ1 — Can AR-enhanced neighborhood explorations increase students’ sense of belonging and spatial literacy in under-resourced urban areas? RQ2 — Which AR designs (historical overlays, future-vision prompts, community-sourced narratives) produce deeper civic engagement? RQ3 — What logistical and ethical barriers limit equitable AR deployment? We will use design-based research across three schools, combine pre/post spatial skill assessments, GPS trajectories, student-created AR content, and focus groups with community partners to iterate prototypes.

23. Peer code-review as formative assessment to accelerate computational thinking in K–12 computer science

We ask: RQ1 — How does structured peer code-review influence novices’ debugging and abstraction skills compared with teacher-only feedback? RQ2 — What biases emerge in peer feedback and how do they affect underrepresented students? RQ3 — Which scaffolds (rubrics, exemplars, auto-detection of common errors) yield the best learning gains? We will run a cluster-randomized trial in classrooms, capture artifacts and review texts, apply NLP to feedback quality, and interview students/teachers to refine peer-review scaffolds.

24. Climate-change storytelling curricula to translate knowledge into local civic action among middle-schoolers

We ask: RQ1 — Does participatory storytelling about local environmental change increase pro-environmental intentions and project initiation? RQ2 — Which narrative frames (personal, scientific, solution-focused) most effectively motivate collective action? RQ3 — How do partnerships with local NGOs influence sustainment of student-led projects? We will implement a quasi-experimental curriculum intervention, code student narratives for framing, measure behavioral intentions and documented community actions, and conduct process evaluation with NGO partners.

25. Wearable biosensor-informed classroom strategies to support self-regulation in neurodivergent learners

We ask: RQ1 — Can teacher-facing summaries of aggregated wearable data (heart rate variability, movement) enable timely, non-stigmatizing support for dysregulated students? RQ2 — What are students’ and families’ ethical perceptions and consent conditions for biosensor use? RQ3 — How do biosensor-informed interventions affect on-task behavior and social-emotional metrics? We will pilot with opt-in cohorts, combine physiological signal processing to detect dysregulation events, run short-cycle interventions, and collect mixed-methods feedback to assess efficacy and acceptability.

26. Gamified faculty-development to shift grading norms from points-based to mastery-oriented assessment

We ask: RQ1 — Does a gamified professional-learning pathway increase faculty adoption of mastery-based grading practices? RQ2 — What changes occur in student learning behaviors and equity outcomes when instructors shift grading norms? RQ3 — Which game mechanics (badges, leveling, peer mentoring) sustain faculty engagement? We will deploy a randomized encouragement design across departments, analyze grade distributions and student performance, survey faculty attitudes longitudinally, and run qualitative case studies of high-adoption instructors.

27. Co-designed anti-deficit STEM curricula integrating Indigenous knowledge systems to improve retention and identity

We ask: RQ1 — How does co-designed STEM curriculum that centers Indigenous epistemologies affect Indigenous students’ STEM identity and persistence? RQ2 — What curriculum features foster reciprocal relationships between school and community knowledge holders? RQ3 — How can assessment practices be adapted to honor multiple ways of knowing? We will use participatory action research with Indigenous elders and teachers to co-create modules, collect longitudinal retention and identity surveys, and analyze classroom discourse with culturally responsive rubrics.

28. Algorithmic-transparency interventions to build students’ algorithmic and data literacy in secondary schools

We ask: RQ1 — Which classroom interventions (visual model-explanations, sandboxed simulators, civic-case analyses) most improve students’ ability to critique algorithmic decisions? RQ2 — How does improved algorithmic literacy influence students’ trust and data-sharing behaviors? RQ3 — What grade-appropriate assessment tasks validly measure algorithmic citizenship? We will design and trial modular interventions, use pre/post standardized tasks and think-aloud protocols, and validate new assessments through item-response analyses.

29. Micro-credential stacking pathways for vocational learners: signaling, equity, and employer recognition

We ask: RQ1 — How do stacked micro-credentials influence employer hiring and promotion decisions in regional industries? RQ2 — Do micro-credential pathways reduce barriers to career mobility for marginalized vocational learners? RQ3 — What governance models ensure portability and transparency of stacks? We will combine employer conjoint experiments, longitudinal tracking of credential earners’ labor-market outcomes, and policy analysis with stakeholder interviews to model effective stacking designs.

30. Silent classrooms: experimental evaluation of minimalist acoustic design on early literacy acquisition

We ask: RQ1 — Does reducing ambient classroom noise through acoustic treatments improve phonological awareness and early reading outcomes? RQ2 — How do teacher vocal strategies change in acoustically optimized spaces and what are secondary effects on teacher well-being? RQ3 — Are low-cost acoustic interventions feasible and equitable across school contexts? We will run a randomized controlled trial installing modular acoustic panels in early-grade classrooms, conduct pre/post literacy assessments, measure noise levels continuously, and interview teachers about instructional and health impacts.

31. Adaptive Peer-Assessment Ecosystems for Culturally Diverse Classrooms

We propose a study of adaptive peer-assessment systems that change feedback norms according to students’ cultural communication styles. We ask: 1) How can adaptive rubrics detect and accommodate high-context versus low-context communicative tendencies in peer feedback? 2) To what extent does culturally adaptive feedback improve learning gains and reduce perceived bias? 3) Which machine- and human-in-the-loop interventions best preserve equity across cultural groups? We will map cultural communication indicators, prototype an adaptive rubric engine, run mixed-method classroom pilots across culturally heterogeneous schools, and analyze learning outcomes, feedback quality, and student perceptions using hierarchical models and thematic analysis.

32. Hybrid Play-Based STEM Curriculum Integrating Low-Cost Haptic Kits

We investigate how affordable haptic kits integrated into play-based lessons affect early STEM concept internalization. We ask: 1) Does embodied haptic interaction accelerate concept formation in preK–2 learners compared with visual-only manipulatives? 2) How do play contexts mediate transfer of haptic experiences to abstract representations? 3) What teacher scaffolds maximize equitable access to haptic learning? We will co-design low-cost kits with teachers, run randomized cluster trials in diverse preschools, collect video-coded interaction data and pre/post concept maps, and iterate kits based on implementation fidelity and equity analyses.

33. Algorithmic Scheduling for Climate-Resilient School Days

We explore algorithmic timetable adjustments to minimize heat- and pollution-related learning loss in climate-vulnerable regions. We ask: 1) Can dynamic scheduling (lesson timing, outdoor vs indoor blocks) guided by real-time environmental data improve cognitive performance and attendance? 2) How do adaptive schedules affect teacher workload and curriculum coverage? 3) What socioethical trade-offs arise when optimizing schedules for environmental risk? We will develop a scheduling optimizer using environmental and attendance datasets, run simulation studies, and implement pilot adaptive schedules in partner districts with physiological measures, standardized assessments, and teacher interviews.

34. Micro-credential Pathways for Adult Learners Using Social Capital Mapping

We examine how mapping learners’ social capital can inform micro-credential pathways that improve employment transitions. We ask: 1) How do localized networks (family, community orgs, employers) predict successful micro-credential uptake and employment outcomes? 2) Can interventions that strengthen weak ties amplify the labor-market value of short credentials? 3) What platform design features best surface social capital opportunities without compromising privacy? We will collect longitudinal survey and social-network data from adult learners, design and test social-capital nudges within a micro-credential platform, and assess employment outcomes via administrative match and causal inference techniques.

35. Multimodal Dyslexia Support Embedded in Augmented Reality Textbooks

We study AR textbooks that dynamically adapt typographic, auditory, and kinesthetic cues to individual dyslexic reading profiles. We ask: 1) Which combinations of multimodal cues most effectively reduce decoding errors and comprehension gaps for varied dyslexia phenotypes? 2) How does in-situ AR support affect learners’ reading motivation and fatigue? 3) What are the teacher adoption barriers and scaffolding needs? We will screen learners for dyslexia subtypes, develop modular AR interventions, run within-subject trials measuring eye-tracking, comprehension, and cognitive load, and conduct teacher co-design workshops for scalable classroom integration.

36. Teacher Identity Development Under Automated Performance Feedback

We investigate how continuous automated classroom analytics (e.g., student attention, discourse metrics) influence teacher identity, agency, and professional growth. We ask: 1) Do automated performance metrics shift teachers’ self-concept, instructional risk-taking, or reflective practices? 2) Which feedback framing (coaching vs evaluative) fosters constructive identity development? 3) How do institutional policies moderate these effects? We will deploy analytics dashboards in volunteer schools with randomized feedback framings, conduct longitudinal interviews and narrative analysis, and model changes in instructional practice and reported professional wellbeing.

37. Language-Mixing Pedagogies for Heritage Learners in STEM Instruction

We examine intentional language-mixing (translanguaging) strategies in STEM lessons to support heritage language maintenance and STEM learning. We ask: 1) Can planned translanguaging improve concept comprehension and identity affirmation for heritage-language STEM learners? 2) What lesson designs (code-switch scaffolds, bilingual glossaries, peer-translation tasks) produce the best dual outcomes? 3) How do teachers negotiate assessment fairness under mixed-language instruction? We will co-design translanguaging modules with bilingual teachers, use quasi-experimental designs across classrooms, assess STEM gains in both languages, and analyze identity markers through interviews and discourse analysis.

38. Civic Reasoning through Augmented Local News Simulations in Secondary Schools

We propose simulating local news ecosystems to teach civic reasoning and misinformation resilience. We ask: 1) Does participation in an augmented local-news simulation improve students’ abilities to trace claims, detect bias, and propose civic remedies? 2) How do role-play identities (reporter, editor, citizen) affect critical evaluation skills? 3) What assessment frameworks validly capture civic reasoning gains? We will build a scalable simulation platform seeded with geolocated data, run semester-long implementations in social studies classes with pre/post civic reasoning instruments, and use natural language processing to evaluate argumentative sophistication.

39. Peer-Led Mental Health First Aid Embedded in Project-Based Learning

We explore integrating peer-led mental health first aid training into ongoing project-based learning (PBL) to normalize support and reduce stigma. We ask: 1) Does embedding MH first-aid roles within PBL teams increase help-seeking and peer support efficacy? 2) How does role rotation affect sustained empathetic practices and academic collaboration? 3) What safeguards ensure psychological safety and appropriate escalation? We will adapt MHFA curricula for PBL contexts, train student peer-responders, measure mental-health literacy, referral rates, and team functioning over time, and evaluate unintended consequences through qualitative case studies.

40. Invisible Barriers: Accessibility of Microlearning for Students with Sensory Processing Differences

We assess how popular microlearning formats (short videos, push-notification quizzes, spaced flashcards) interact with sensory processing differences to create hidden accessibility barriers. We ask: 1) Which sensory features (tempo, contrast, haptic alerts) trigger aversion or overload for different sensory profiles? 2) How can microlearning platforms offer minimally intrusive personalization that preserves serendipitous learning? 3) What educator practices mitigate exclusion when microlearning is adopted at scale? We will recruit learners with documented sensory profiles, conduct usability testing across common microlearning modules, measure engagement and learning retention, and produce design guidelines and plugin prototypes for adaptive sensory controls.

41. Ambient soundscapes in teacher education: How curated classroom sound environments shape novice teachers’ in-the-moment pedagogical decisions

We consider this an underexplored area in teacher training. Research questions: How do different ambient soundscapes (natural sounds, low-level human chatter, white noise, silence) influence novice teachers’ micro-decisions (asking follow-ups, calling on students, pacing)? To what extent do soundscapes interact with teacher stress and working memory to change instructional choices? We propose a mixed-methods field experiment in teacher-training classrooms where we randomize soundscapes, collect think-aloud protocols and video-coded decisions, and triangulate with physiological stress markers and post-session interviews.

42. Micro-feedback timing from AI tutors: Longitudinal effects of sub-10-second feedback on student metacognition in undergraduate STEM

We frame this as a practical but little-studied temporal granularity question. Research questions: Does ultra-short (≤10s) AI feedback during problem solving improve students’ metacognitive monitoring and calibration over a semester compared with standard feedback? What feedback content optimizes long-term transfer? We will run a semester-long randomized controlled trial across lab sections with instrumented problem sets, log-file analysis of response latencies and revisions, pre-post metacognitive inventories, and follow-up transfer tests.

43. Cultural semiotics of emoji use in asynchronous academic discussion boards and effects on peer assessment accuracy

We treat emoji as understudied cues in formal learning spaces. Research questions: How do students from different cultural-linguistic backgrounds interpret emoji in peer feedback? Do emoji-laden comments bias peer grading or perceived helpfulness? We will conduct a cross-cultural vignette experiment combined with discourse analysis of real course forums, recruiting diverse student cohorts, and measuring interpretive variance, rating shifts, and qualitative rationales.

44. Role-reversal VR modules for teaching conflict resolution: Behavioral change and classroom transfer in middle school students

We believe immersive role-reversal offers unique empathy-building potential. Research questions: Does a VR experience where students inhabit the perspective of the peer they previously conflicted with reduce future conflict recurrence and increase prosocial conflict strategies? How durable are behavioral changes across a school year? We will co-develop VR scenarios with teachers, implement pre-post behavioral observations, incident logs, teacher reports, and focus groups to assess transfer to real-world interactions.

45. Invisible curricular labor: Quantifying adjunct faculty curriculum adaptation work and its impact on student learning outcomes

We identify this as a largely invisible contribution in higher education. Research questions: How much unpaid time do adjuncts spend adapting curricula for diverse student needs, and how does that adaptation relate to measurable student outcomes (retention, grades, engagement)? We will use time-use diaries, structured interviews with adjuncts across departments, and link reported adaptation activities to institutional student outcome data using multilevel models.

46. Tactile-only digital STEM textbooks: Effects on problem-solving strategies among students with visual impairments

We see a need for rigorous comparison of tactile interfaces in STEM learning. Research questions: How do tactile-only digital textbooks affect conceptual problem-solving accuracy, strategy use, and cognitive load compared with audio and multimodal versions? What design affordances most support spatial reasoning in tactile formats? We will prototype tactile interactions (haptic diagrams, embossed math), run controlled usability and performance studies with visually impaired students, and analyze strategy transcripts and performance metrics.

47. Classroom biodiversity and neurodiversity: Does increased plant diversity support attention restoration and inclusive STEM identity for neurodivergent students?

We find ecological design in classrooms is rarely evaluated for neurodivergent learners. Research questions: Does introducing varied, low-maintenance plant biodiversity in classrooms improve sustained attention, reduce sensory overload, and shape STEM identity among neurodivergent students relative to standard décor? We will implement a quasi-experimental design across matched classrooms, administer attention tasks, collect sensory sensitivity and identity surveys, and conduct teacher-student ethnographies.

48. Co-created rubrics: Effects of students co-designing assessment rubrics with teachers on assessment literacy and perceived fairness

We consider co-design an actionable intervention for assessment literacy. Research questions: Does the process of co-designing rubrics increase students’ assessment literacy, self-regulation, and trust in grading? How does co-design influence rubric reliability when applied by peers? We plan an action-research cycle in multiple classrooms where we facilitate co-design workshops, measure pre-post assessment literacy, run inter-rater reliability studies, and gather reflective journals from participants.

49. Algorithmic recommendation transparency for admissions officers: How explanatory interventions change holistic evaluation practices

We approach admission decision-making as socio-technical and under-researched regarding transparency. Research questions: Does providing admissions officers with varying levels of algorithmic explanation (feature importance, counterfactuals, uncertainty) alter their holistic judgments, reliance on algorithmic advice, or equity-conscious filtering? We will simulate an admissions review lab with mock applications, randomized transparency conditions, think-aloud protocols, and analysis of decision shifts and justification patterns.

50. Narrative datafication of learning histories: Effects of transforming student data into visual stories on motivation, agency, and privacy perceptions

We take a critical design perspective on student-facing analytics. Research questions: How does presenting a student’s aggregated learning history as a visual narrative (timeline, annotated milestones) affect motivation, self-efficacy, and sense of agency compared with raw dashboards? What privacy concerns and consent preferences arise when personal learning stories are generated for others (parents, teachers)? We will design narrative prototypes, conduct randomized exposure studies measuring motivational and agency outcomes, and run in-depth interviews about privacy trade-offs and consent design.