Nontraditional Approaches with Nontraditional Students: Experiences of Learning, Service and Identity Development
Bibliographic record
Abstract
Nontraditional students are a growing population in higher education, yet our understanding of the unique factors that predict their success have not increased. Economic challenges, changing work demands, and the desire for personal and professional advancement fuel the nontraditional student's return to school (Kelly & Strawn, 2011). Their isolation and lack of social networks lead to poor academic outcomes as defined by retention, graduation and degree attainment. The classroom offers a beacon of hope for the engagement of nontraditional students, an opportunity to strengthen student identity and draw connections across the multiple worlds where these students reside. This phenomenological inquiry examined the lived experiences of highly nontraditional students enrolled in credit-bearing, undergraduate higher education courses, that used pedagogy related to service and learning and the effects of this pedagogical intervention with attention to civic and student identity, reflecting the extent to which students perceive these identities as marginalized. The central question explored was: To what extent did experiences of learning and service contribute to the civic and student identities of highly nontraditional students? Using Saddington's (1998) dimensions of experience in adult learners' lives, the learner's life experience is utilized for integration, not only as a source of knowledge but also as the content of the curriculum. This research added concepts from Weil and McGill's (1989) Four Villages of Experiential Learning and from Identity Development theory (Tajfel & Turner, 1986). Adult learners' Outgroup and Ingroup identities produce experiences related to personal perceptions, societal power, and validity in roles. Adult learners have vast cultural and contextual experience, as well as pre-constructed meaning schemes (Knowles, 1998, 1990) and service connects to community role identities, and can trigger the exploration and redefinition of identities (Mezirow, 1997; Hogg, 2004; Tajfel & Turner, 1986). Adult learner identity is drawn from multiple sources, past and present, and shaped by beliefs that are contradictory in nature (Kasworm, 2005). Findings include the inherent challenges for this student population related to their Outgroup status, the advantages of pedagogy that uses service and learning, the importance of opportunities for intergroup exchange, and the need for specific faculty roles.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".