Commentary: Downloaded lectures have been shown to produce better assessment outcomes
Notice bibliographique
Résumé
I am accustomed to full lecture theaters when I lecture, and this is the first year that my class attendance for science-major students has dropped to around 70%. This is not the case for medical lectures that still attract full participation even though they are recorded. Medical students are motivated to attend by vocational focus and by mandated attendance. My science lectures are recorded both for audio and slide presentation. After a decade of rapture with my laser pointer, I have now taken to use the mouse as a pointer to highlight the regions of my slides that I am talking to. This achieves a number of advantages. It records the mouse highlighting for students replaying the lecture, it allows me to keep facing the audience while I look at the monitor in front of me, and it works on all of the screen displays in our large lecture theaters. The capture of all the information in my lectures leaves little value to be added by attending my lectures; perhaps being able to ask questions, although email can do that. With relevance to our current students, I have observed that when commuting by public transport, there is a near complete use of audio–visual devices by the plugged-in under 30 age group. New technology, new generation, and new allocations of time to work and study are combining to diminish lecture attendances. Some colleagues refuse to make lecture recordings available, but that strikes me as a Luddite's denial of the new reality. If the students learn effectively then there is no problem with allowing them to manage their own learning activities. It may even be that lecture attendance is counterproductive because there is evidence that the university students who downloaded a podcast lecture achieved higher assessment results than those who attended the lecture in person [1]. McKinney et al [1]. presented 64 students with a single lecture on visual perception from an introductory psychology course. The paper can be accessed by a link at www.fredonia.edu/department/psychology/mcKinneyhp.asp. Half of the students attended the class in person and received a printout of the slides from the lecture (they did not get access to the podcast). The other 32 downloaded a podcast of the same lecture, synchronized with video of the slides, and received a printed handout of the material. When tested a week later, students who received the podcast averaged 71%, whereas those who attended the lecture averaged 62%. In further analyzing the podcast group, the lower achievers watched the podcast but did not take notes, whereas the highest achievers viewed the podcast multiple times and took notes. Podcasted lectures offer students the chance to replay difficult parts of a lecture and therefore take better notes. Some blog comments on the McKinney paper [2] include “Worst is the lectures where the lecturer reads from his PowerPoint slides (which are made available for download)—absolutely no point in attending. Of course, often these lecturers also use the same exam paper they have for the last 10 years as well. So, the real title of the McKinney article should have been “Quality of teaching at some universities now so poor students learn more by not attending class.” Another commentator wrote “it was a biased, commercially influenced, poorly conducted study” to which the lead author (McKinney) replied “I am curious to know if you read my actual article, or merely the blog posts that tell you a very simplistic version of the study? It was published in a peer reviewed journal.” McKinney indeed appreciated the limitations of her study and added a lot of useful research background in her paper with a good selection of references. On balance, I am prepared to accept that students can perform as well from taking a virtual lecture as a real lecture. From the view of the students, it remains the case that learning is largely driven by assessment, so if the examination goals are clear then virtual lectures can adequately teach a course. If a virtual lecture can have better outcomes than a real time lecture then it makes sense to select the best virtual lectures in the world to offer in a course. Apple Computers Inc. have 30 years of providing computer support for universities and realized that it was a good fit with their iPod business to add podcasts of lectures frompremier universities. From 2005, Stanford has attracted two million downloads of lectures via iTunes. “At Stanford, we are always seeking innovative ways to share knowledge. We want to convey an intellectually dynamic experience in a way that a newspaper article or an abstract in a scholarly journal simply can't achieve. With iTunes U, we believe the excellence of Stanford can be seen, heard, and felt in a compelling way by a huge audience. It's unlikely that Jane and Leland Stanford could have imagined a world where the iPod is ubiquitous, and where such reach is possible. But I think they would be proud that the university has not been afraid to outgrow old thoughts and ways, daring to think along new lines as it pursues knowledge in service to the public good” [3]. The portal to get iTunes lectures is not as simple as going to a web site like YouTube. You must open the iTunes application from Apple, go to the Apple Store, and then search iTunes U. If a target is known then easier access is possible. For example, if you wish to sample UC Berkeley's Molecular and Cell Biology 110 (General Biochemistry and Molecular Biology) run by Randy Schekman, Tom Alber, Q. Zhou, and E. Nogales then have iTunes running and log onto the URL deimos3. apple.com/WebObjects/Core.woa/Browse/berkeley.edu. 1622385355.02413789580. iTunes U is available to any higher-education institution in the US, Canada, Australia, Ireland, New Zealand, and UK. In Australia, my university (Melbourne, http://trs.unimelb.edu.au/itu/) has a public channel on iTunes U providing access to lectures of international interest, whereas Griffith University provides iTunes lectures (including biochemistry) that can be downloaded across several campuses and multiple courses such as nursing and science. Applying the Cloud-computing model [4], Apple hosts the data on iTunes U and administrators get weekly spreadsheet reports from Apple on site usage and content popularity. The sustained growth in quantity and quality of iTunes University offerings and the widespread decline in student attendances are pointing to a virtual future for an increasing amount of undergraduate teaching.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».