The Relationship between Performance Feedback and Service-Learning.
Notice bibliographique
Résumé
Performance Feedback and Service-Learning Rooted in the civics education tradition in American schools (Hepburn, 1997), service-learning is receiving interest from academicians in higher education interested in applying curricular models that are experience-based (Gabelnick, 1997) and socially responsive (Altman, 1996). There is evidence that effective service-learning programs lead to such beneficial outcomes as increases in students' self-esteem (Eyler & Giles, 1997), systemic and complex moral reasoning (Eyler, Root, & Giles, 1998), development of productive interpersonal relationships with adults (McGill, 1992), and commitment to help others (Giles & Eyler, 1994). Moreover, service-learning experiences help students face the reality of working with other adults on problems encountered in the community. These experiences could, therefore, be valuable in building competencies to work effectively with co-workers and customers (Stone & Mortimer, 1998) and making career choices (Owens, 1982). Also, service-learning programs, like internships, could help in crystallizing students' vocational self-concepts (Hall, 1976), thereby easing their transition from school to work (Kramer, 1974), and allowing them access to potential employers. Performance feedback has been described as a developmental tool for students participating in service-learning (Menlo, 1993), and has been treated as a principle of good practice in the service-learning literature (Honnett & Poulson, 1989). Feedback in the work setting could potentially impact students involved in service-learning in at least three ways. 1. Adaptation. There is evidence that feedback facilitates individual adaptation in the workplace (Ashford, 1986). Feedback forms a significant part of an organization's information environment (Hanser & Muchinsky, 1978), providing people with information regarding performance standards, rules, and norms, as well as the extent to which these are being met or not met. This helps people develop strategies to attain desired goals and other workplace standards, and ultimately leads to successful adaptation. 2. Insight. According to the experiential learning perspective (Dewey, 1938; Lewin, 1951; Marsick, 1991), performance feedback can help people gain insight into their own values, beliefs, and assumptions about people and work, especially if their experiences are processed through reflection (Marsick, 1989). Similarly, 360-degree feedback research suggests that feedback can help enhance people's awareness about their competencies, thus facilitating personal change and development (Yammarino & Atwater, 1997). 3. Self-Efficacy. Performance feedback available to individuals through enactive mastery and verbal persuasion have been shown to enhance self-efficacy (Bandura, 1986). Higher levels of self-efficacy might lead individuals to set more challenging goals and attempt more complex strategies to achieve goals, and increase the probability of successfully attaining these goals. In the service-learning context, self-efficacy would be translated into better student performance, as well as higher student confidence in addressing community problems and choosing challenging careers. Although the positive impact of feedback on performance in training programs has been demonstrated in various studies (e.g., Martocchio & Dulebohn, 1994; Martocchio & Webster, 1992), little is known about how performance feedback specifically impacts the way in which people learn from their experiences in the natural context of their workplace. Studies of feedback and training performance cannot be easily generalized to the realm of experiential learning in the workplace because of the unstructured and often random characteristics of such learning (Marsick, 1990), and because what is learned may or may not be directly translated into changes in objective performance. On the other hand, this type of learning is extremely common and has implications for the individual's adaptation to the work environment and to self-development. …
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,013 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».