Community Based Participatory Research: A Ladder of Opportunity for Engaged Scholarship in Higher Education
Bibliographic record
Abstract
Higher Education the world over is recognized as a driver of development in the knowledge based economy. It is believed that Higher Education benefits the economy through the formation of human capital and building a knowledge base that contributes to solving problems in society. However, voices of frustration about graduates being unable to relate theory to practice in different contexts raises questions about the quality of teaching and learning in Higher Education Institutions (HEI). Some reports have shown that graduates seem to leave HEI’ s disengaged, ill equipped, and unable to apply acquired university knowledge to real world problems. In addition, even though the mission of the university is inclusive of engagement among others, community engagement priority seems to be emphasized only on the part of faculty members and less so on students. This in part is a result of a curriculum that mainly promotes classroom based learning and the ivory tower mentality of HEI, which places the community in the periphery of knowledge and data production. This conceptual paper argues that in order for HEI’s to produce quality graduates, who are innovative and active citizens, a transformative teaching and learning scholarship that moves beyond “classroom-based theory” is necessary, more especially for students in applied fields of study such as community development. Borrowing from Nyerere’s educational philosophy, this paper posits that Community Based Participatory Research (CBPR), with its collaborative inquiry, social action and service learning, may provide a basis for engaged scholarship of teaching and learning that promotes engagement for higher education students in applied fields of study. Thus, by exploring the concepts of engaged scholarship and CBPR and the nuances that exist between them, this paper seeks to underscore the importance of CBPR and how it can contribute to engaged scholarship for students.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.212 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.004 |
| Science and technology studies | 0.021 | 0.080 |
| Scholarly communication | 0.029 | 0.030 |
| Open science | 0.007 | 0.054 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".