College Students in an Experimental Study Took Longer to Achieve Comprehension when Instant Messaging while Reading
Notice bibliographique
Résumé
A Review of: Bowman, L. L., Levine, L. E., Waite, B. M., & Gendron, M. (2010). Can students really multitask? An experimental study of instant messaging while reading. Computers & Education, 54, 927-931. Objective – To examine the effects of multitasking while doing school work. The experiment specifically measured total time spent reading a simulated textbook passage and tested comprehension in students who received instant messages before reading, while reading, or not at all. Design – Experimental design in which one group of students read an online text while receiving and responding to instant messages. Comparison groups either received instant messages (IMs) prior to reading the text passage or did not receive any IMs during the task. Setting – General psychology department at Central Connecticut State University, United States. Subjects – Eighty-nine college students enrolled in general psychology courses. The participants included 43 women and 46 men and were between 17 and 46 years old. Most students were full time students (91%), most were European / White (74%) and in their first (46%) or second (33%) year of college. Participants’ academic majors represented all the schools in the university. Methods – Researchers created a simulated environment in which a passage from a psychology textbook was displayed on five consecutive screens. For the experimental group, an IM appeared on each of the five screens preceded by an alert sound. Messages were written to reflect the types of questions students might ask each other when they first meet, such as “What do you like to do in your spare time?” Subjects were randomized to three situations: receiving IMs before reading, receiving IMs during reading, or not receiving any IMs. Subjects were told that they would either receive IMs before reading, while reading, or not at all. Messages received during reading appeared one per screen after a specified time spent on each page (after 17, 15, 29, 20 and 26 seconds, respectively.) Students could take as long as necessary to read the passage and to respond to IMs. After reading the passage, students were given a multiple choice test with 25 questions to determine reading comprehension and retention. Students also completed a demographic questionnaire to measure their typical instant messaging behaviour, including the amount of time they spend each week instant messaging, how often IM software is on when their computer is on, and how often IM software is on when they are studying. Both of these activities took place on the same computers used for the reading experiment. Students were additionally asked to comment on the clarity of instructions, the representativeness of the task to their typical IM experiences, and the interest and similarity to normal coursework of the reading itself. These questions were asked on paper rather than on the computer. Software recorded the lengths of time each student spent in reading the passage, reading and responding to IMs, and answering the online questions. For those students who received IMs during reading, the time spent from receipt of each IM to each response was subtracted from the total reading time. Main Results – There were no differences in test performance between the three groups. Statistically significant differences were found in the amount of time that students took to complete the reading: students who instant messaged during reading took significantly longer to read the online text than those students who instant messaged before reading and those who did not IM, even when time spent receiving and responding to IMs was subtracted from the totals. Students who instant messaged before reading took the least amount of time in the exercise. Further statistical analysis revealed no significant differences in the time spent instant messaging between the two IM groups. Responses to the demographic questions indicate that students spend a mean 7.5 hours instant messaging per week, that 67% of students have IM software on “sometimes,” “often,” or “very often” while the computer is on and 62% of the time while studying. Analysis indicated that none of the IM use variables were correlated with test performance or reading time and that there were no significant differences between the experimental groups according to prior IM use. Responses from the 77 students who answered the questions about the experiment itself are also included, though not all of these students answered each question. Seventy students (99%) agreed or strongly agreed that instructions were clear. Seventy-one percent of the 52 students that received IMs agreed or strongly agreed that they were realistic, and 75% agreed or strongly agreed that they responded to IMs in a typical manner. Sixty-two students (82%) agreed or strongly agreed that the text was similar to those assigned for actual coursework, and 39 students (51%) agreed or strongly agreed that the passage was interesting. Students commented on the authenticity of the experiment in free text responses such as, “I responded how I would have to anyone,” and “they were questions that anyone I don’t know might ask.” Conclusion – This experimental study suggests that students who IM while reading will perform as well but take longer to complete the task than those who do not IM while reading or those students who IM before reading.
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,005 |
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 ».