Assessment strategies for the on-line class : from theory to practice
Notice bibliographique
Résumé
EDITORS' NOTES (Rebecca S. Anderson, John F. Bauer, Bruce W. Speck).1. Learning-Teaching-Assessment Paradigms and the On-Line Classroom (Bruce W. Speck):Professors need to engage in rigorous design and assessment of on-linelearning just as they would in face-to-face and printed materials,grounding their decisions in solid pedagogical theory and practice.2. What Professors Need to Know About Technology to Assess On-Line Student Learning (Marshall G. Jones, Stephen W. Harmon):There is much movement in the direction of on-line learning, but it isimportant to consider the nature of on-line courses and the extent towhich that nature determines what is done by instructors and students.3. Assessing Student Work from Chatrooms and Bulletin Boards (John F. Bauer):An advantage of on-line learning is that it can provide a permanentrecord of student participation in discussions. The question addressedin this chapter is how to assess that participation fairly and objectively.4. Assessing Students' Written Projects (Robert Gray):Because so much of student work on-line is done in written format, itis important for instructors to know how to evaluate writing and howto take advantage of the technology to do it.5. Group Assessment in the On-Line Learning Environment (John A. Nicolay):Just as group work is becoming more and more prevalent in collegeclassrooms, it is also a growing part of on-line learning. This chapterprovides five principles for assessing group work on-line.6. Assessing Field Experiences (Jane B. Puckett, Rebecca S. Anderson):In professional preparation programs that feature a great deal of fieldwork,can on-line formats be used to monitor and assess student work?7. Enhancing On-Line Learning for Individuals with Disabilities (James M. Brown):One of the advantages of on-line instruction is that it provides accessfor students who would not normally be able to participate in manycourse activities. This chapter provides guidelines on how to takeadvantage of this feature.8. Assessing E-Folios in the On-Line Class (Mark Canada):On-line instruction provides an excellent opportunity for students tocreate and publish on-line portfolios of their work. This method ofassessment is just beginning to make inroads into the on-line environment.9. Preparing Students for Assessment in the On-Line Class (Michele L. Ford):Just as instructors are adapting to new technologies, students mustadjust their thinking about teaching and learning. This chapter providessuggestions about how to help students make the transition to on-lineassessment.10. Assessing the On-Line Degree Program (Joe Law, Lory Hawkes, Christina Murphy):As more programs are offered on-line, it is important that institutionsmaintain the quality of those offerings. This chapter describes guidelinesfor assessing the integrity and quality of such degrees.11. Assessing the Usability of On-Line Instructional Materials (Brad Mehlenbacher):In addition to the quality of the content and instructional method, anumber of other considerations are useful in assessing whether on-linematerials will be effective. This chapter covers a wide range of criteriafor instructor use in this task.12. Epilogue: A Cautionary Note About On-Line Assessment (Richard Thomas Bothel):Not all instructors are enthusiastic about the movement toward on-linelearning. This chapter raises some concerns that should be addressednow.INDEX.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,025 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,008 | 0,007 |
| Science ouverte | 0,005 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,007 |
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 source (Gemma direct ou Codex distillé), 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 ».