Experiential Learning Spaces for Enterprise Resource Planning Courses in Business Schools
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
Enterprise Resource Planning (ERP) systems have experienced mainstream adoption as a comprehensive solution for business function integration and end-to-end process management. To meet industry demand, many business schools offer academic courses in ERP strategy and technology to train students to be proficient in the use of ERP systems. The extant literature on ERP education highlights the need for additional research about pedagogical techniques that can help business schools in their efforts. To be effective in the delivery of ERP courses, instructors require a deeper understanding of how they can teach ERP systems in a meaningful way and consequently foster higher levels of student engagement. This paper provides an overview of the current state of ERP academic programs and teaching practices. This is followed by a review of experiential learning theory (ELT) which is later used in this paper as a basis for pedagogical practice suggestions towards the improvement of ERP training. A pedagogical model comprising of various course activities and teaching practices is proposed. The proposed practices are justified in terms of their efficacy towards developing experiential learning spaces for students to cultivate theoretical and applied knowledge of ERP systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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