Designing our Thinking: Examining the Effects of Experiential Learning and Design Thinking on Creativity, Innovation, and Collaboration Skills Development in the Undergraduate Classroom
Bibliographic record
Abstract
This paper shares initial findings from a study of the way that design thinking and experiential learning informed approaches to teaching can help programs and institutions in the higher education community meet the teaching and learning objectives identified by the World Economic Forum (WEF) as critical for our global future. The project surveyed undergraduate students in a large first year introductory course to learn more about how design thinking based learning practices might serve to extend an experiential learning pedagogical approach toward the successful development of innovation, creativity, interpersonal, self-paced, problem-based and lifelong learning skills. Results from the survey of 600 students reveal that using a design thinking model of learning as part of an experiential learning curriculum may be an effective way to enhance the development of the identified skills and approaches within an experiential learning framework. Students who experienced the addition of design thinking based learning practices to an experiential learning framework reported higher levels of confidence in their innovation and creativity skills and were more likely to seek opportunities for collaboration and self-paced learning than those who participated in an experiential learning focused section of the same class. This article provides an illustration of the impact of using design thinking as an extension of experiential learning in an undergraduate higher education class and offers recommendations for institutions and professional programs seeking to meet World Economic Forum Education 4.0 Initiative goals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.015 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".