Experiential Learning to Teach User Experience in Higher Education in Past 20 Years: A Scoping Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Experiential learning is an effective method to teach User Experience (UX) to Human-Computer Interaction (HCI) students. Despite its popularity, there seems to be no comprehensive overview on (1) the current use of experiential learning in UX education at universities and (2) student learning outcomes and benefits resulting from the use of experiential learning. Hence, we conducted a scoping review to provide such overview. We analyzed 45 articles published from 2000 to 2021 and we found 12 types of experiential learning employed by HCI educators: applied research project, industry/community research project, hands-on activity, role-play, interactive workshops, guest speakers, in-house work placement, internship, flipped classroom, field project, lab, and design hackathon, from most to least frequent. Twenty-six articles reported student learning outcomes and benefits: (1) enhanced UX technical knowledge, (2) applied textbook knowledge into practice, (3) acquired soft skills, (4) student satisfaction, (5) increased awareness of user diversity, and (6) increased job marketability. Overall, we advance current HCI teaching practices by providing HCI educators with a list of experiential learning types that they can adopt in their classes to teach UX.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it