The Journal of information and systems in education 

About: The Journal of information and systems in education is an academic journal. The journal publishes majorly in the area(s): Information system & Curriculum. Over the lifetime, 823 publications have been published receiving 15721 citations.

Teaching Tip: The Flipped Classroom.

Abstract: 1. INTRODUCTION In a traditional instructor-centered classroom, the teacher delivers lectures during class time and gives students homework to be done after class. In a flipped, or inverted, classroom, things are done the other way round: the teacher "delivers" lectures before class in the form of pre-recorded videos, and spends class time engaging students in learning activities that involve collaboration and interaction. Passive learning activities such as unidirectional lectures are pushed to outside class hours, to be replaced with active learning activities in class. The term "inverted classroom" appeared in the literature as early as 2000 (Lage, Platt and Treglia, 2000) and was made popular by Chemistry teachers Bergmann and Sams in recent years (Bergmann and Sams, 2012, 2012a). With successful similar implementations of web-based lecture technologies--the often quoted success stories being the Khan Academy and Massive Open Online Courses--the flipped classroom gained traction at educational institutions in North America across a spectrum of disciplines and at different levels of instruction. This pedagogy has also been consistently rated as one of the top trends in educational technology (for example, Watters, 2012). Some educators have reported lower failure rates (Michigan Radio, 2013), greater flexibility, lesser stress (NBC, 2013), improved student attitudes and even better test scores (Flipped Learning Network, 2012) for classes that adopted this model. However, being a relatively new trend, most implementations of the flipped classroom are reported in blogs, online magazines and newspapers instead of academic papers and conferences. There seems to be little rigorous research done to measure the effects of this pedagogy (Goodwin and Miller, 2013), and what has been published so far seems far from conclusive. Whilst a 3-year long study of flipped learning for a pharmaceutics course reported a 5.1% improvement in student performance (Meyer, 2013), contradictory preliminary data from another 3-year study at Harvey Mudd College suggest that flipping may not cause any difference in student outcomes (Atteberry, 2013). Adding to the debate, a recent study (Schneider, Wallace, Blikstein and Pea, 2013) concludes that students who engage in open-ended exploration first outperformed those who used traditional textbook materials first, and implies that video lectures and textbooks should come after exploration, and not before (Plotnikoff, 2013). Despite the controversy, this pedagogy's raising popularity has motivated the author to run a trial on a class of 46 Information Systems (IS) undergraduates during a special term in 2013. The course that this class was taking is a second course in programming that covered object-oriented design and advanced programming. In previous years, this course was usually conducted in "interactive seminar" style: instructors taught a new concept and reinforced what they had just taught via short hands-on programming exercises performed on students' laptops. Instructors then moved on to the next concept and the cycle was repeated. Longer programming exercises would then be given as optional homework that could be submitted for feedback from teaching assistants. Whilst such interactive seminars were more effective than traditional monologue-style lectures (Steinert and Snell, 1999), the author observed that some students were still not engaged. Many students were updating their Facebook pages during the teaching sessions. Students who visited the washroom could miss a critical part of the lecture. Slower students who had difficulty picking up the concepts during the "first parse" were consequently unable to successfully complete the hands-on exercises that followed. For these students, the course rapidly snowballed into a vicious cycle of disengagement, poor performance, lack of confidence, and further disengagement. It was hoped that the flipped classroom could increase students' engagement with the content and improve their overall experience with the course. …

Tweeting the Night Away: Using Twitter to Enhance Social Presence

Abstract: To be truly effective, online learning must facilitate the social process of learning. This involves providing space and opportunities for students and faculty to engage in social activities. Although learning management systems offer several tools that support social learning and student engagement, the scope, structure, and functionality of those tools can inhibit and restrain just-in-time social connections and interactions. In this teaching tip, we describe our use of Twitter to encourage freeflowing just-in-time interactions and how these interactions can enhance social presence in online courses. We then describe instructional benefits of Twitter, and conclude with guidelines for incorporating Twitter in online courses.

The Role of Social Presence and Moderating Role of Computer Self Efficacy in Predicting the Continuance Usage of E-Learning Systems

Abstract: The continuous growth of the electronic learning (e-learning) market has drawn a lot of discussion about the effectiveness of virtual learning environments (VLE). The initial emphasis of e-learning in the context of information technology skills training continues to be relevant. The success of an e-learning program in information technology (IT) may require users to be equipped with a certain degree of computer self-efficacy and affect for information systems. These factors may, in turn, influence the satisfaction level of online learners and their intention to continue using the e-learning system. Therefore, it is plausible that these factors may be as important as or more important than the design of an effective VLE in an IT context. This paper blends the Computer Self-Efficacy (CSE) and Expectation-Confirmation Models (ECM), and assesses their applicability on the intention of online learners who continue using the e-learning system as a vehicle to assimilate IT skills. Second, it theorizes the causal relationship of the factors of Perceived Usefulness, Confirmation, Satisfaction, and IS Continuance in the e-learning context. Finally, it assesses the relative importance of social presence in helping online learners to prevail over the online asynchronous environment. Our results indicate that, in the context of assimilating IT skills, there is not a significant relationship among the CSE of online learners, their perceived usefulness, confirmation, and satisfaction level. As a moderating factor, computer self-efficacy does not have significant influence on learning outcomes. For knowledge long transfer, social presence was shown to have an effect in different VLEs.

An Enhanced Technology Acceptance Model for Web-Based Learning

Abstract: Although information technology (IT) has played an increasingly important role in contemporary education, resistance to IT remains significant in the education sector. This study attempts to identify additional key determinants of the IT acceptance in the education sector based on a study in which. 280 full-time teachers who were part-time students of a bachelor degree program participated. The current technology acceptance model (TAM) and the social cognitive theory (SCT) are combined to provide a new framework for this analysis. Results of the study are consistent with the TAM factors for explaining behavioral intention. The study also indicates that the computer self-efficacy (CSE) has substantial influence on the teachers’ technology acceptance. Implications of the resulting factors are discussed within the context of education.

Examining the Affects of Student Multitasking with Laptops during the Lecture

Abstract: 1. INTRODUCTION Laptop computers are widely used in many college classrooms today (Weaver and Nilson, 2005); however, there is an ongoing debate regarding the purpose and value of laptop initiative programs that encourage or even require students to purchase laptops, and the role of laptops in classrooms. Although the use of laptops in the classroom has the potential to motivate and contribute to student learning (Efaw, Hampton, Martinez, Smith, 2004; Trimmel and Bachmann, 2004), they also have the potential to negatively impact student attention, motivation, student-teacher interactions, and academic achievement (Young, 2006; Meierdiercks, 2005). Previous research has shown that students who bring laptops to class often engage in electronic multitasking that involves switching their cognitive focus back and forth between tasks that are directly related to the lecture material and tasks that are not directly related to the lecture material (Fried, 2008; Hembrooke and Gay, 2003; Grace-Martin and Gay, 2001). Although many students may believe they can switch back and forth between different tasks with no serious consequences to their academic performance, multitasking has been shown to dramatically increase the number of memory errors and the processing time required to "learn" topics that involve a significant cognitive load (Rubenstein, Meyer, and Evans, 2001). Attempting to "learn" while engaged in multitasking behavior can result in the acquisition of less flexible knowledge that cannot be easily recalled and/or applied in new situations (Foerde, Knowlton, and Poldrack, 2006). Furthermore, it takes time and effort to refocus after switching from one task to another (Bailey and Konstan, 2006). It can be argued, that multitasking is a natural part of the modern classroom and work environments and students need to learn to multitask effectively--especially in today's high tech world. Research that investigates how students use laptops in the classroom and what affects laptop usage has on performance outcomes does exist, but there is a lack of research that focuses on the unstructured or unsanctioned use of computers in the classroom, that explicitly measures learning outcomes, and that incorporates actual use data (1). In general, multitasking has been shown to negatively impact productivity (Foerde, Knowlton, and Poldrack, 2006; Rubenstein, Meyer, and Evans, 2001); however, the affects of different types of computer-based multitasking behaviors in the classroom have not been measured and examined in detail to date. This paper presents the results of an exploratory study that investigates different types of student multitasking behavior while using laptop computers in an unstructured manner during class. A number of novel contributions are made. First, we collect both self reported laptop usage data and actual laptop usage data from spyware installed on student laptops. This allows us to directly measure student laptop use, and then compare student's actual usage to self-reported usage. Second, we categorize different types of software multitasking activities and identify which activities are performed most frequently and for how long. We then examine how different categories of distractive software activity impact class performance. We define distractive multitasking as tasks or activities where cognitive resources are used to process information that is not directly related to the course material. Productive multitasking is defined as tasks or activities that are directly related to completing a primary task associated with the course material. Finally, we introduce quantifiable metrics for measuring the frequency, duration, and extent of student multitasking behavior in class, and evaluate the impact this behavior has on academic performance. Three primary research questions are addressed. (1) How does the frequency of multitasking related to each multitasking category affect learning outcomes? …