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The Impact of a Technology Ban on Students’ Perceptions and Performance in Introduction to Psychology
Abstract
To test the impact of the implementation of technology bans on students’ experience within a course, we collected data from four sections of Introduction to Psychology at a small liberal arts college in the northeast. In two sections, students were banned from using personal technology devices during lecture. In the other two sections, students were permitted to use personal technology devices freely during lecture. We found a significant reduction in student engagement but not in reported interest in psychology or perceived professor–student rapport for students in the technology-ban condition relative to students in the technology-permitted condition. In contrast to previous studies, we found no difference in final grade performance across condition. Although further research is needed, these results suggest that instructors should consider the composition of students in their course prior to implementing a technology ban in the classroom.
... In response to this challenge, several studies have explored pedagogical approaches for the effective use of technology in higher education settings which combine a reduction in distraction and an increase in student engagement. Prevalent approaches include incorporating technology-related guidelines and policies into course syllabi and prohibiting technology usage during classes (Elliott-Dorans, 2018;Hutcheon et al., 2019). Research has shown that college students consider stricter strategies (e.g., grade reduction, removal from class) to be more effective in reducing their off-task behaviors than more lenient strategies (e.g., verbal whole-class warning, technology-related policies on syllabi; Berry & Westfall, 2015). ...
... However, although strict penalties and implementation of no-technology policies can effectively reduce digital distraction, students report feeling that these strategies restrict their personal freedom (Redner et al., 2020), and such strategies also have the greatest negative impact on student-instructor relationships (Finn & Ledbetter, 2014). Simply enforcing bans on technology usage without implementing additional strategies to promote student engagement can have adverse effects and hinder student learning (Elliott-Dorans, 2018;Hutcheon et al., 2019). For these reasons, instructors often hesitate to ban technology usage from their classrooms . ...
... Although instructors recognize the consequences of digital distraction, they often hesitate when to ban technology usage from their classrooms . Simply enforcing bans on technology usage without implementing additional strategies to promote student engagement can have adverse effects and hinder student learning (Elliott-Dorans, 2018;Hutcheon et al., 2019). To effectively integrate technology into classrooms, college instructors need to consider strategies such as using visual prompts for maximizing students' learning and minimizing students' digital distractions. ...
Technology is recognized as a valuable learning tool, but research indicates that students are also distracted by the use of technology in class. Since college students constantly rely on their devices for learning, it has become imperative for instructors to find effective ways of integrating technology into their lessons while reducing digital distractions. In this study, we investigated the effects of behavior strategies related to in-class device usage among undergraduate students. Students were provided with visual prompts corresponding to various class activities to direct their use of devices in class. At the end of the semester, we surveyed the students about their perspectives on the visual prompts strategy for device usage. The majority of students found value in the use of technology devices in class for their learning (efficient work, notetaking, concentration) and indicated overall positive effects of the visual prompts strategy. For successful technology integration in college classrooms, instructors should consider using strategies such as visual prompts to enhance students’ learning experience and reduce digital distraction.
... Nevertheless, some attempts have been made to find educational strategies or interventions aiming to prevent multitasking and its deleterious effects on learning such as requiring students to turn off their smartphones or put them on vibrate mode (Carrier et al., 2015), banning technologies during in-person classes (Elliott-Dorans, 2018;Hutcheon et al., 2019;Vahedi et al., 2019), informing students about the deleterious effects of multitasking (Tassone et al., 2020), or introducing "technology breaks" during lectures (Guinness et al., 2018). Although some of these appear to be useful strategies, those based on prohibition are without any effects or are counter-productive. ...
... A radical strategy has also been used, consisting in preventing students from using their devices during lectures by banning technologies during in-person classes. However, findings suggest that banning technologies during lectures in the absence of complementary efforts to increase engagement can be counter-productive, including on learning performance (Elliott-Dorans, 2018;Hutcheon et al., 2019;Vahedi et al., 2019). Other educational strategies have been examined to reduce multitasking activities during in-person classes. ...
Multitasking activities among students using various technological devices is common during lectures, and many studies have demonstrated their deleterious effects on various learning outcomes. In contrast, fewer studies have examined ways to reduce multitasking and stimulate engagement in learning. The present study provides an educational strategy to reduce student multitasking during lectures by displaying the teacher’s slideshow on the students’ devices. In the control condition, students visualized the teacher’s slideshow only on the lecture hall screen by means of a video projector. In the experimental condition they also had the possibility to visualize the teacher’s slideshow on their own device in real time. Independently of the students’ level of knowledge and their location in the lecture hall, results revealed that fewer multitasking activities were performed and affective engagement was higher in the experimental than in the control condition. Furthermore, the relationship between slideshow display and affective engagement was mediated by the number of multitasking activities. These findings demonstrate a useful strategy to prevent multitasking during lectures and to promote engagement in learning among students using a digital environment in which the teacher’s slideshow is synchronized on the students’ devices.
... 15,81 Besides this, university students are considered to be adult learners, who desire autonomy in learning. 1,2,82 Students, as part of the digital generation, desire the freedom to deliver what they have learned to their environment, from the internet access they have. 83 Based on the results of this study and the SCT, the individual aspect (P), the self-regulation variable, has no direct significant effect on academic cyberslacking (H2). ...
Introduction
University students, as members of the digital generation, often access the internet for non-academic purposes while attending lectures in the classroom. Internet access for non-academic purposes during lectures is known as academic cyberslacking. This study aims to test the effects of media multitasking, self-efficacy, self-regulation, social media engagement, and Attention, Relevance, Confidence, and Satisfaction (ARCS) motivation, on the engagement in academic cyberslacking by university students.
Methods
The participants were 1485 university students, who had previously engaged in academic cyberslacking during lectures. The research instruments in this study were an academic cyberslacking scale, a media multitasking self-efficacy scale, a self-regulation scale, a social media engagement scale, and an ARCS motivation scale. The research model and hypotheses are tested using structural equation model (SEM) by Lisrel. Confirmatory factor analysis (CFA) is also used to analyze all the instruments. The respondents’ demographic data were analyzed using SPSS.
Results
The results showed that it is only media multitasking self-efficacy and social media engagement which have any significant effects regarding academic cyberslacking. Self-regulation and ARCS motivation do not have direct association with academic cyberslacking.
Conclusion
Students do academic cyberslacking during lectures. Media multitasking self-efficacy and social media engagement can predict students’ academic cyberslacking. It is recommended that students direct their involvement in the digital environment to more constructive efforts during lectures.
... Many studies examining the impact of screens on undergraduate learning have been completed in controlled settings (e.g., Mueller & Oppenheimer, 2014). Only a few scientific studies have looked at the impact of screen-free zones in undergraduate classrooms (i.e., Aguilar-Roca et al., 2012;Carter et al., 2017;Hutcheon et al., 2019), suggesting additional ecologically valid studies of this kind are needed. Further, to our knowledge, no studies have reported student satisfaction with the arrangement, as measured by formal instructor evaluations. ...
Background
With in-person instruction, many undergraduates look at screens during lectures. Because screens can distract, attempts to curb this behavior through screen policies are increasingly common but understudied.
Objective and Method
Two quasi-experimental studies (Study 1: N = 412; Study 2: N = 179) in the same Psychology class explore results of restricting screens to one area of the classroom on exam performance and instructor/course evaluation.
Results
In both studies, these policies improved exam scores in the class. In Study 2, students who chose to sit in the screen-free zone did better on exams. Limiting screen use to the back of the classroom (Study 1) produced student pushback in qualitative comments and lower evaluations in quantitative instructor and course ratings. In contrast, placing screen and screen-free zones side-by-side (Study 2) was accepted without comment by students.
Conclusion
Together, these studies suggest that creating screen-free zones in classrooms can be beneficial for students, especially for those students who choose to sit in the screen-free section. Additionally, students accept side-by-side division of a classroom into screen and screen-free zones.
Teaching Implications
Because these studies are ecologically valid, results have implications for how students take notes and how instructors set restrictions on screens in their classroom.
... De leur côté, les enseignants se disent souvent tentés de restreindre ou interdire les technologies dans les salles de classe. Des recherches récentes montrent pourtant des effets négatifs de cette interdiction : les étudiants à qui on avait interdit d'utiliser leur ordinateur portable disent aussi avoir été moins engagés dans les cours, moins assidus, et ont obtenu de moins bons résultats académiques par rapport à ceux qui avaient été autorisés à l'utiliser [Elliott-Dorans, 2018 ;Hutcheon et al., 2019]. Bien que des recherches supplémentaires soient nécessaires, les études suggèrent qu'interdire l'utilisation des appareils technologiques dans les cours n' est peut-être pas la meilleure solution pour engager les étudiants dans les apprentissages. ...
Un article de vulgarisation.
Dans l'enseignement en présentiel, faut-il intégrer ou interdire les technologies dans les cours en amphis (ou dans les salles de classe)?
Référence:
Michinov, N. (2020). Le dilemme des technologies dans les amphis. Palimpseste, 3, 47-51.
... Research on laptop use during lectures explored the relation between laptop use, multitasking, student attention, and performance. Laptops are widely used by students for note-taking and their effects have been debated widely, with some lecturers calling for an outright ban on laptops in the lecture room (Elliott-Dorans 2018;Fink 2010;Hutcheon, Lian, and Richard 2019;Young 2006). In an analysis of student surveys, Fried (2008) found that 78 of the 128 students used a laptop during the lectures and that 81% of these students checked their email during lectures, 68% used instant messaging, 43% surfed the net, 25% played games and 35% did 'other things' (910). ...
This paper presents an analysis of a hundred and one handwritten essays by master students in Informatics. The students reflected on their experiences of working with pen and paper for reading and writing as a mandatory assignment for the duration of a five-week intensive course. Taking an inductive approach, reflexive thematic analysis was used to identify patterns of meaning across the full dataset. The essays elicited insightful student reflections on learning, knowing, and being. One overarching theme, New connections, and four sub-theses were identified: Handwriting as note making, Being present for learning, Freedom to think, and Materiality of reading and writing. This study contributes to an improved understanding of the affordances of paper and laptops in the lecture room, based on a student-centred approach, and reflects on how student perspectives can be implemented during lectures.
... While neighbor distraction alone may not encourage students to engage in cyberloafing, it may increase the perception of in-class norms and thus cause more students to engage in this behaviour. The use of laptops may also have other deleterious effects, such as a decrease in student engagement in class [24], and the contribution to inefficient study habits [18]. ...
A student’s ability to learn effectively in a classroom setting is subject to many factors. While some factors are difficult to regulate, this study explores two factors that a student, or instructor, has full control over, namely 1) seating position, and 2) computer usage. Both factors have been studied considerably with regard to their effects on student performance, and the results indicate that sitting further from the instructor, or using a computer in the classroom, are related to a decline in grade performance. However, it is unclear if the choice of where to sit and whether or not to use a computer in class are mediated by the same cognitive process. If they are the same, then we would expect to see an interaction between the factors, such that, for example, computer usage would most negatively impact the grades of students who sit near the back of a class. This study aims to answer this question by looking at the individual and combined effects of seating position and computer usage on classroom performance. We sampled 1364 students, collecting nearly 3000 total responses across 5 different introductory psychology courses with 4 different instructors on 3 separate occasions. In agreement with previous research, we found that sitting further from the instructor negatively impacted students' grades (0.75 percentage points/row), and using a computer in class negatively impacted grades (by 3.88 percentage points). Our novel finding is that these deleterious effects combined in an additive manner, such that using a computer had the same harmful effect on grade performance regardless of whether the student sat at the front or back of the classroom.
... Our students' responses suggested that they were more relaxed about forms of disruptiveness involving in-class use of personal technologies as compared with traditional disruptive behaviors. Given that college students appear to hold mostly negative views of restrictions on personal technology during class time, an outright ban may not be an effective strategy (Hutcheon, Lian, & Richard, 2019). ...
Online surveys examined college instructors’ and students’ attitudes about in-class use of personal mobile devices (e.g., phones, laptops). Instructors (Study 1: N = 125, 64.2% graduate students) who were more sensitive to traditional disruptions (e.g., arriving late) were more sensitive to technology-related disruptions (e.g., texting). Attitudes toward personal devices in relation to learning were negatively associated
with perceived disruptiveness. Policies to restrict devices were related to perceived frequency, but not disruptiveness, of technology-related disruptions. Students (Study 2, N = 174) reported that classroom disruptions from personal devices were infrequent and considered it more important for instructors to set policies for traditional disruptions than for use of personal devices. In Study 3, students (N = 187) reported attitudes about academic use of personal devices at the beginning of an introductory course and distraction from devices at the end of the course. Distractibility was associated with lower quiz scores but was unrelated to attitudes about devices. Nontraditional students (≥�24 years) reported less media multitasking and had higher quiz scores than traditional students but did not differ in attitudes about devices. Given their divergent views, instructors and students should communicate more about the potential for personal devices to disrupt the learning process.
... De leur côté, les enseignants se disent souvent tentés de restreindre ou interdire les technologies dans les salles de classe. Des recherches récentes montrent pourtant des effets négatifs de cette interdiction : les étudiants à qui on avait interdit d'utiliser leur ordinateur portable disent aussi avoir été moins engagés dans les cours, moins assidus, et ont obtenu de moins bons résultats académiques par rapport à ceux qui avaient été autorisés à l'utiliser [Elliott-Dorans, 2018 ;Hutcheon et al., 2019]. Bien que des recherches supplémentaires soient nécessaires, les études suggèrent qu'interdire l'utilisation des appareils technologiques dans les cours n' est peut-être pas la meilleure solution pour engager les étudiants dans les apprentissages. ...
Qu’ils vivent en famille d’accueil ou en foyer, la plupart des adolescents relevant de la protection de l’enfance, comme tous ceux de leur âge, possèdent aujourd’hui un smartphone. Alors que les mesures de placement cherchent à séparer les lieux de vie pour leur permettre de se reconstruire loin d’un milieu familial jugé inadapté, cet outil technologique constitue un cordon relationnel, qu’ils peuvent gérer de manière autonome. Quels usages en font-ils ? Peut-on les considérer comme bénéfiques ou au contraire comme dangereux ?
En l’absence de consignes officielles précises, les professionnels de la protection de l’enfance (assistants familiaux, éducateurs, référents, coordinateurs, juges…) doivent trouver de nouveaux ajustements pour faire cohabiter pratiques juvéniles, communications familiales et mesures de protection. À partir d’une analyse des décisions de justice et de la réalité des pratiques, les auteurs montrent les marges de manœuvre possibles entre le maintien d’un cadre formel et l’élaboration d’un accompagnement qui tient compte du parcours familial des enfants et des innovations socionumériques.
... Elliott-Dorans reported that students who were banned from using their laptops had lower class attendance and lower grades on both papers/coursework and examinations, across both semesters, compared to students who were permitted to use their laptops. In another study by Hutcheon et al. (2019), students in two sections of a course were allowed to use ICTs in the classroom, whereas those in two other sections were banned from using their ICTs. They found no significant differences between the two groups on students' exam grades, professor-student rapport, or interest in the course. ...
Research has frequently found that students use their information and communication technologies—such as smartphones and laptops—for non-academic uses in the classroom. These uses include sending messages as well as checking email and social media accounts. This study aimed to examine students’ in-class information and communication technology use, their motivations for it, and perceptions of it, as well as their attitudes toward restriction and integration of information and communication technologies in the classroom. It was found that students most frequently engage in non-academic information and communication technology use when they feel that they would not miss any new class content, or when they feel disengaged. Students perceived that their non-academic information and communication technology use had costs, especially distraction. However, students also reported negative attitudes toward policies that would restrict their information and communication technology use in the classroom but had positive perceptions of attempts to integrate information and communication technology use. We propose that information and communication technology integration can be an effective method of increasing student engagement—and therefore decreasing non-academic information and communication technology use.
The role of rapport facilitating cooperation and information disclosure has been widely acknowledged by both researchers and practitioners across professional information‐gathering contexts. However, the definition and assessment of rapport are still debated, resulting in a lack of reliable and commonly used tools to effectively measure rapport. This review explored how rapport has been measured in professional information‐gathering contexts and illustrates key characteristics of published measures in a searchable systematic map. A total of 111 research articles and 126 measures of rapport were evaluated based on standards in scale development and validation. The measures' conceptualisation of rapport was also examined with their individual items being coded for the following theorised components of rapport: (i) paying attention, (ii) personalising the interview/interaction, (iii) being approachable and (iv) establishing a mutual connection. Findings are synthesised and discussed in relation to the overarching patterns found, including limited consistency and validity in current measures of rapport.
Laptop use within college courses has been a topic of debate for nearly two decades. Completely banning laptops from college classes may seem appealing given the potential drawbacks, but these policies may have unintended consequences. One seemingly successful intervention that can address these conflicting goals is the use of laptop zones and laptop-free zones which allows students who want to use their laptops to continue to do so, without hindering the performance of those who do not. We examine the efficacy of this intervention through the lens of the theory of self-regulated learning. We implemented laptop(-free) zones in two large college courses with a total of 168 students, 60 of whom reported sitting in a laptop-zone. Students sitting in the laptop-free zone performed better on objective measures of learning on the day of learning new material, but this difference was not significant five days later on a measure of retention. Further, there were no differences between these groups on self-rated performance at the point of retention. By examining open-ended responses regarding their motivation to sit in the laptop-free zone or the laptop-zone, we found students who sat in the laptop-free zone typically reported wanting to avoid distractions and enhance their memory of the material/class performance compared to those who sat in the laptop zone. Also, more individuals who sat in the laptop zone reported doing so to ensure completeness of their notes, to look up extra course-related material, and to complete non-course related tasks while listening to the lecture. Lastly, we pose of set of future directions aimed at learning more about the use of laptops in and outside of class, and how we can help students be successful using laptops for learning.
Why do some students excel in their college classes and develop interest in an academic discipline? The authors examined both the short-term and long-term consequences of students' achievement goals in an introductory psychology course. Mastery goals positively predicted subsequent interest in the course, but not course grades. Performance goals positively predicted grades, but not interest. Three semesters later, the authors obtained measures of continued interest in the discipline and long-term performance. Mastery goals predicted subsequent enrollment in psychology courses, whereas performance goals predicted long-term academic performance. These positive and complementary effects of mastery and performance goals on different measures of academic success are consistent with a multiple-goals perspective in which both goals can have beneficial consequences in college education.
In the present study, we examined the relations between daily in-class cell phone use and test grades among college students. Across 2 semesters and 6 separate courses, participants (N = 218; 174 females, 44 males; 50 freshmen, 54 sophomores, 76 juniors, and 38 seniors; Mage = 20.0 years, age range 18–23 years) completed a brief questionnaire at the end of each class period indicating the number of times they used their cell phone for social networking (e.g., email, texting, using Facebook), to access the Internet for information, for organization (e.g., update one’s calendar), or to play a game. Mixed-effects regression model analyses indicated that cell phone use was significantly and negatively associated with test scores regardless of student sex and grade point average (β = −0.287, p = .035). We discuss the results in terms of the ubiquitous nature of cell phone use among today’s wired generation and the implications it has for learning, achievement, and postcollege success. (PsycINFO Database Record (c) 2015 APA, all rights reserved). Direct link: http://psycnet.apa.org/psycarticles/2015-45218-001.pdf&productCode=pa
It is well documented that interacting with a mobile phone is associated with poorer performance on concurrently performed tasks because limited attentional resources must be shared between tasks. However, mobile phones generate auditory or tactile notifications to alert users of incoming calls and messages. Although these notifications are generally short in duration, they can prompt task-irrelevant thoughts, or mind wandering, which has been shown to damage task performance. We found that cellular phone notifications alone significantly disrupted performance on an attention-demanding task, even when participants did not directly interact with a mobile device during the task. The magnitude of observed distraction effects was comparable in magnitude to those seen when users actively used a mobile phone, either for voice calls or text messaging. (PsycINFO Database Record
(c) 2015 APA, all rights reserved).
This paper reports on a study that examined the use of wireless laptops for promoting active learning in lecture halls. The study examined students’ behavior in class and their perceptions of the new learning environment throughout three consecutive semesters. An online survey revealed that students have highly positive perceptions about the use of wireless laptops, but less positive perceptions about being active in class. Class observations showed that the use of wireless laptops enhances student-centered, hands-on, and exploratory learning as well as meaningful student-to-student and student-to-instructor interactions. However, findings also show that wireless laptops can become a source of distraction, if used for non-learning purposes.
Laptops are commonplace in university classrooms. In light of cognitive psychology theory on costs associated with multitasking, we examined the effects of in-class laptop use on student learning in a simulated classroom. We found that participants who multitasked on a laptop during a lecture scored lower on a test compared to those who did not multitask, and participants who were in direct view of a multitasking peer scored lower on a test compared to those who were not. The results demonstrate that multitasking on a laptop poses a significant distraction to both users and fellow students and can be detrimental to comprehension of lecture content.
The authors investigated faculty and student perceptions regarding the use of cell phones and other electronic devices in the classroom. Students differed markedly from faculty, with students exhibiting much greater acceptance of in-class use of technology. Among students, the authors found that gender affected perceptions. Specifically, male students were more accepting of in-class use of technology than were female students. Also, graduate students were more disturbed by off-task use of laptop computers in class than their undergraduate counterparts. This research should be of interest to postsecondary educators and administrators in attempting to bridge the student-faculty generation gap, and in formulating policies regarding the use of electronic devices in the classroom.
This paper presents results of a study that examined the effect of different levels of autonomy upon intrinsic goal orientation, task value, self-efficacy, test anxiety, use of metacognitive strategies, and performance in the college classroom. Study participants were 365 college students from 4 institutions in 10 classrooms: 3 biology (n=162); 3 English (n=79); and 4 social science classes (n=124). Study findings revealed clear differences between the three types of classrooms on end-of-term mean levels of intrinsic goal orientation, task value, and self-efficacy, with autonomy showing a facilitative effect on these constructs. Metacognition was only slightly, but positively related to autonomy. Neither test anxiety nor performance seemed to be related to classroom experiences of autonomy. Both intrinsic goal orientation and autonomy were significant main effects on end-of-term task value; and intrinsic goal orientation and autonomy seemed to have an additive relationship with regard to task value. Intrinsic goal orientation, but not autonomy, was related to differences in end-of-term levels of metacognition and self-efficacy. The results indicate that the effects of autonomy are more closely related to motivation than to actual performance. Contains 17 references. (Author/GLR)
Individual response technology (IRT), in which students use wireless handsets to communicate real-time responses, permits the recording and display of aggregated student responses during class. In comparison to a traditional class that did not employ IRT, students using IRT performed better on exams and held positive attitudes toward the technology. IRT appears to be a promising technology for increasing active learning in the classroom and enhancing students' mastery of course content.
We tested whether a utility value intervention (via manipulated relevance) influenced interest and performance on a task and whether this intervention had different effects depending on an individual's performance expectations or prior performance. Interest was defined as triggered situational interest (i.e., affective and emotional task reactions) and maintained situational interest (i.e., inclination to engage in the task in the future). In 2 randomized experiments, 1 conducted in the laboratory and the other in a college classroom, utility value was manipulated through a writing task in which participants were asked to explain how the material they were learning (math or psychology) was relevant to their lives (or not). The intervention increased perceptions of utility value and interest, especially for students who were low in expected (laboratory) or actual (classroom) performance. Mediation analyses revealed that perceptions of utility value explained the effects of the intervention on interest and predicted performance. Theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Why do some students excel in their college classes and develop interest in an academic discipline? The authors examined both the short-term and long-term consequences of students' achievement goals in an introductory psychology course. Mastery goals positively predicted subsequent interest in the course, but not course grades. Performance goals positively predicted grades, but not interest. Three semesters later, the authors obtained measures of continued interest in the discipline and long-term performance. Mastery goals predicted subsequent enrollment in psychology courses, whereas performance goals predicted long-term academic performance. These positive and complementary effects of mastery and performance goals on different measures of academic success are consistent with a multiple-goals perspective in which both goals can have beneficial consequences in college education. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
THE EFFECTS OF MULTITASKING IN THE CLASSROOM were investigated in students in an upper level Communications course. Two groups
of students heard the same exact lecture and tested immediately following the lecture. One group of students was allowed to
use their laptops to engage in browsing, search, and/or social computing behaviors during the lecture. Students in the second
condition were asked to keep their laptops closed for the duration of the lecture. Students in the open laptop condition suffered
decrements on traditional measures of memory for lecture content. A second experiment replicated the results of the first.
Data were further analyzed by “browsing style.” Results are discussed from Lang’s Limited Process Capacity model in an attempt
to better understand the mechanisms involved in the decrement.
Path analysis was used to examine the relationship between class start times, sleep, circadian preference, and academic performance in college-aged adults. Consistent with observations in middle and high school students, college students with later class start times slept longer, experienced less daytime sleepiness, and were less likely to miss class. Chronotype was an important moderator of sleep schedules and daytime functioning; those with morning preference went to bed and woke up earlier and functioned better throughout the day. The benefits of taking later classes did not extend to academic performance, however; grades were somewhat lower in students with predominantly late class schedules. Furthermore, students taking later classes were at greater risk for increased alcohol consumption, and among all the factors affecting academic performance, alcohol misuse exerted the strongest effect. Thus, these results indicate that later class start times in college, while allowing for more sleep, also increase the likelihood of alcohol misuse, ultimately impeding academic success.
We conducted a neuropsychological and cognitive assessment study to determine whether time of day affects cognitive performance. We measured executive control (fluency), processing speed, semantic memory, and episodic memory performance. We followed 56 students across 3 different times of day, testing performance on vocabulary, fluency, processing speed, and episodic memory. Results showed an advantage for fluency and digit symbol task performance in the afternoon and evening testing times relative to morning testing (regardless of testing order), but that time of day did not affect semantic or episodic memory performance. These results suggest that optimal executive functioning and processing speed may occur for typical college students in the afternoon and evening regardless of time-of-day preference.
The goals of this study were to extend the literature about classroom autonomy in several ways. First, since previous research on autonomy has tended to focus on younger learners, we examined whether the positive effects of autonomy on motivation and performance would be replicated in a college sample. Second, we tested to see whether the well-established links between intrinsic motivation and autonomy would also be found using motivational constructs that play key roles in learning (specifically, task value, self-efficacy, and test anxiety). Third, we sought to trace the effect of autonomy on changes in student motivation over the course of a semester. Finally, we examined the role of autonomy on course performance. We found that experiences of classroom autonomy in the college classroom were more closely related to motivational factors than to performance. While the immediate experience of autonomy may not be directly facilitative of high course grades, autonomy does seem to foster intrinsic goal orientation, task value, and self-efficacy, all of which are critical components of "continuing motivation." The data presented here lend further support for the benefits of fostering autonomy within academic settings.
Laptop computers are widely prevalent in university classrooms. Although laptops are a valuable tool, they offer access to a distracting temptation: the Internet. In the study reported here, we assessed the relationship between classroom performance and actual Internet usage for academic and nonacademic purposes. Students who were enrolled in an introductory psychology course logged into a proxy server that monitored their online activity during class. Past research relied on self-report, but the current methodology objectively measured time, frequency, and browsing history of participants’ Internet usage. In addition, we assessed whether intelligence, motivation, and interest in course material could account for the relationship between Internet use and performance. Our results showed that nonacademic Internet use was common among students who brought laptops to class and was inversely related to class performance. This relationship was upheld after we accounted for motivation, interest, and intelligence. Class-related Internet use was not associated with a benefit to classroom performance.
We present findings from a study that prohibited computer devices in randomly selected classrooms of an introductory economics course at the United States Military Academy. Average final exam scores among students assigned to classrooms that allowed computers were 0.18 standard deviations lower than exam scores of students in classrooms that prohibited computers. Through the use of two separate treatment arms, we uncover evidence that this negative effect occurs in classrooms where laptops and tablets are permitted without restriction and in classrooms where students are only permitted to use tablets that must remain flat on the desk.
In this article, I address the paradox that university grade point averages have increased for decades, whereas the time students invest in their studies has decreased. I argue that one major contributor to this paradox is grading leniency, encouraged by the practice of university administrators to base important personnel decisions on student evaluations of teaching. Grading leniency creates strong incentives for instructors to teach in ways that would result in good student evaluations. Because many instructors believe that the average student prefers courses that are entertaining, require little work, and result in high grades, they feel under pressure to conform to those expectations. Evidence is presented that the positive association between student grades and their evaluation of teaching reflects a bias rather than teaching effectiveness. If good teaching evaluations reflected improved student learning due to effective teaching, they should be positively related to the grades received in subsequent courses that build on knowledge gained in the previous course. Findings that teaching evaluations of concurrent courses, though positively correlated with concurrent grades, are negatively related to student performance in subsequent courses are more consistent with the assumption that concurrent evaluations are the result of lenient grading rather than effective teaching. Policy implications are discussed.
Motivation theory suggests that autonomy supportiveness in instruction often leads to many positive outcomes in the classroom, such as higher levels of intrinsic motivation and engagement. The purpose of this study was to determine whether perceived autonomy support and course-related intrinsic motivation in college classrooms positively predict student ratings of instruction. Data were collected from 47 undergraduate education courses and 914 students. Consistent with expectations, the results indicated that both intrinsic motivation and autonomy support were positively associated with multiple dimensions of student ratings of instruction. Results also showed that intrinsic motivation moderated the association between autonomy support and instructional ratings—the higher intrinsic motivation, the less predictive autonomy support, and the lower intrinsic motivation, the more predictive autonomy support. These results suggest that incorporating classroom activities that engender autonomy support may lead to improved student perceptions of classroom instruction and may also enhance both student motivation and learning.
Rapport between students and teachers leads to numerous positive student outcomes, including attitudes toward the teacher and course, student motivation, and perceived learning. The recent development of a Professor-Student Rapport scale offers assessment of this construct. However, a Cronbach's a of.96 indicated item redundancy, and the 34-item scale is unwieldy in a survey-heavy culture. In addition, the most valuable outcome of student learning is actual grades, which remained to be assessed. In the current study, we relied on principal component analysis to reduce the number of items on the Professor- Student Rapport scale and examine predictive power of fewer items. We measured traditional student outcomes such as attitudes, motivation, and perceived learning. We also assessed end-of-semester grades to remove any potential student bias in learning or grade reporting. Six rapport items concerning student engagement and enjoyment of a course predicted all student outcomes, including course grades.
We surveyed undergraduates to learn the extent to which they experience rapport with their instructors, assess the relation between rapport and student attitudes and behaviors, and determine instructor qualities and behaviors that appear related to establishing rapport. Most students reported experiencing rapport with at least 1 teacher and indicated that rapport is positively related to their enjoyment of the teacher and subject matter. They also reported that rapport motivates them to engage in several proacademic behaviors.
Taking notes on laptops rather than in longhand is increasingly common. Many researchers have suggested that laptop note taking is less effective than longhand note taking for learning. Prior studies have primarily focused on students' capacity for multitasking and distraction when using laptops. The present research suggests that even when laptops are used solely to take notes, they may still be impairing learning because their use results in shallower processing. In three studies, we found that students who took notes on laptops performed worse on conceptual questions than students who took notes longhand. We show that whereas taking more notes can be beneficial, laptop note takers' tendency to transcribe lectures verbatim rather than processing information and reframing it in their own words is detrimental to learning.
Student engagement is considered an important predictor of student achievement, but few researchers have attempted to derive a valid and reliable measure of college student engagement in particular courses. In 2 studies, we developed and explored the validity of a measure of student engagement, the Student Course Engagement Questionnaire (SCEQ). Exploratory factor analysis revealed 4 dimensions of college student engagement that were distinct and reliable: skills engagement, participation/interaction engagement, emotional engagement, and performance engagement. We reported evidence of the convergent and discriminant validity of the measure. In particular, we found relationships between factors on the SCEQ and self-report measures of engagement, endorsement of self-theories, goal preferences, and grades.
The proliferation and ease of access to information and communication technologies (ICTs) such as Facebook, text messaging, and instant messaging has resulted in ICT users being presented with more real-time streaming data than ever before. Unfortunately, this has also resulted in individuals increasingly engaging in multitasking as an information management strategy. The purpose of this study was to examine how college students multitask with ICTs and to determine the impacts of this multitasking on their college grade point average (GPA). Using web survey data from a large sample of college students at one university (N = 1839), we found that students reported spending a large amount of time using ICTs on a daily basis. Students reported frequently searching for content not related to courses, using Facebook, emailing, talking on their cell phones, and texting while doing schoolwork. Hierarchical (blocked) linear regression analyses revealed that using Facebook and texting while doing schoolwork were negatively associated with overall college GPA. Engaging in Facebook use or texting while trying to complete schoolwork may tax students' capacity for cognitive processing and preclude deeper learning. Our research indicates that the type and purpose of ICT use matters in terms of the educational impacts of multitasking.
The past several decades have witnessed an impressive array of studies that have attempted to identify and explain the factors important to the success and failure of students as they pursue a college education. The extent of this effort is not surprising given the impact that level of education has on a variety of life domains (Pascarella & Terenzini, 2005) and given the difficulties universities have in retaining students (Braxton, 2001; Tinto, 1993). College success has been variously defined with a focus upon either performance outcomes, such as grades for individual courses or semesters; outcomes such as college persistence, often measured over one or two semesters; and, less frequently, degree attainment.
Many of these studies have been guided by educational or engagement theories of student success (e.g., Bean, 1985; Tinto, 1993). These theories have focused upon student involvement in college and propose a distinctly contextual perspective: success is influenced by the degree to which students become engaged and involved in academic and other activities of college life. These engagement approaches emphasize what individuals do and what institutions do to encourage and support individual student involvement. Astin’s (1984) definition of student involvement captures the centrality of student actions and behaviors in engagement theorizing as well as the scope of behaviors that could reflect engagement: student involvement “refers to the amount of physical and psychological energy that the student devotes to the academic experience” (Astin, p. 297).
Previous studies have often broadly measured academic engagement including such components as, for example, time- and task-management skills (Garavalia & Gredler, 2002; Trockel, Barnes, & Egget, 2000), seeking help from peers (Larose, Robinson, Roy, & Legault, 1998), and interactions with professors (Strage, 1999). Thus, academic engagement is broadly conceived and captures not just course-related activities (e.g., class attendance, completion of assignments) but includes broadly defined involvement in academic life. Additionally, engagement is often measured by student intentions or perceptions of academic engagement, often captured by single items assessed at a single point in time. Although these measures provide important information regarding student intentions or perceptions, they do not necessarily inform us about students’ actual engagement behaviors.
To address measurement shortcomings of single items representing a complex content domain, Handelsman, Briggs, Sullivan, and Towler (2005) explored the structure of a subset of academic engagement, student engagement in a single course. They developed a multi-item scale representing course engagement and analyzed the factor structure on a sample of students enrolled in a course. Their results indicated that although academic course engagement is multidimensional, containing emotional, participatory, and performance components, there is a single and large dimension that measures a skill-effort component. This first skill-component factor that emerged included items about going to class, doing reading assignments, studying notes, and generally putting forth academic effort.
This skill-effort component of engagement has been found to be reliably related to various measures of college success. Robbins et al. (2004) provided an integrative meta-analytic review of the degree to which engagement behaviors predict college success. Outcomes were categorized along two dimensions: college academic performance measured by GPA and retention or persistence toward a degree. The authors categorized over 100 studies along nine constructs assumed to relate to college success. One of these constructs, termed academic-related skills, was defined as “activities necessary to organize and complete schoolwork tasks, and to prepare for and take tests” (p. 264). Similar in content to Handelsman et al.’s (2005) first factor of engagement, it was found to relate to college performance, and somewhat surprisingly, even more strongly to retention. Furthermore, academic-related skills demonstrated incremental validity in predicting retention after the inclusion of other engagement constructs such as social involvement, institutional commitment, and social support. Based upon these unexpectedly robust relations of academic-related skills and retention, Robbins et al. concluded that engagement models of persistence may underestimate the importance of skill- and effort-focused academic engagement in college student retention. Moreover, they proposed that theoretical clarity and the interpretability of future empirical findings will be enhanced by more narrowly measured constructs with more psychometrically sound measurement.
Therefore, the present study specifically focused more narrowly on student engagement as defined by academic course involvement and effort directed toward...
Rapport traditionally has been measured in therapy or in other one-on-one relationships such as with roommates. As yet, no scale is available to measure professor–student rapport. In this study, 51 undergraduates created items to measure professor–student rapport, and subsequently, 195 different college students rated their agreement with items based on their professor. Factor analysis revealed 1 meaningful component of professor–student rapport represented by 34 items. Rapport correlated with professor immediacy, providing convergent validity. Hierarchical linear regression with immediacy entered first and rapport entered second revealed significant improvement in prediction of student attitudes toward the instructor and the course as well as student motivation, perceptions of learning, and self-reported grades. Thus, we propose that professor–student rapport as measured by the current scale serves as a useful predictor of valuable student outcomes.
Recently, a debate has begun over whether in-class laptops aid or hinder learning. While some research demonstrates that laptops can be an important learning tool, anecdotal evidence suggests more and more faculty are banning laptops from their classrooms because of perceptions that they distract students and detract from learning. The current research examines the nature of in-class laptop use in a large lecture course and how that use is related to student learning. Students completed weekly surveys of attendance, laptop use, and aspects of the classroom environment. Results showed that students who used laptops in class spent considerable time multitasking and that the laptop use posed a significant distraction to both users and fellow students. Most importantly, the level of laptop use was negatively related to several measures of student learning, including self-reported understanding of course material and overall course performance. The practical implications of these findings are discussed.
Rapport: Its relation to student attitudes and behaviors toward teachers and classes
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relation to student attitudes and behaviors toward teachers and
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Technology bans and student experience in the college classroom
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the college classroom. In W. Altman, L. Stein, & J. E. Westfall
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I'm banning laptops from my classroom
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Today's lesson: Life in the classroom before cell phones
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Katz, L. (2014, August). Today's lesson: Life in the classroom before
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Leave your laptops at the door to my classroom. The New York Times
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