Toward an Integrative Understanding of Information Technology Training Research across Information Systems and Human-Computer Interaction: A Comprehensive Review
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Notice bibliographique
Résumé
Researchers investigating issues in the domain of training and human-computer interaction share a common interest in ensuring that users are skilled in the use of Information Technologies (IT). When users have the necessary skills, they can utilize IT productively and also have a pleasant human-to-computer interaction. Over the past three decades, Information System (IS) researchers have made considerable efforts in identifying the most effective ways to develop users’ IT skills. However, at this point in time, there are many changes taking place in the IT environment and organizations find it challenging to keep their employees trained and updated on IT skills. Hence, it is important for the IS community to respond by taking the lead in identifying and conducting research that can help organizations effectively address these challenges. We take the first step in conducting a comprehensive review of training research published in major IS and HCI journals over the past three decades so as to synthesize IT training research, provide an integrative understanding of findings, and propose directions for future research. Our study indicates that while IS research on training has made steady progress in advancing our understanding of alternative IT training methods and cognitive learning processes, it also has several shortcomings. Past research has: a) focused primarily on the training program without sufficient attention to activities prior to and after the program, b) used a small set of theoretical foundations, and c) focused on a few topics and on single-user systems rather than integrated enterprise systems. Critical issues such as improving user motivations prior to training, transfer of training skills to the workplace, assessment of training, and supporting user learning that occurs after training have not been given adequate attention. We identify several research opportunities by tapping into relatively unexplored theories and urge researchers to continue research to address the gaps identified in this comprehensive review as well as to develop innovative methods to help employees learn through newer channels, such as e-learning and social media.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,006 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,008 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,003 |
| 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 découle