Abstract:Think-pair-share (TPS) is a classroom active learning strategy in which students work on activities, first individually, then in pairs and finally as the whole class. TPS allows students to express their reasoning, reflect on their understanding and obtain prompt feedback on their learning. While TPS is recommended to foster classroom engagement and learning, there is a lack of research based evidence in computer science education on the benefits of TPS for learning. In this study, we investigate the learning … Show more
“…iSAT visualizes proportions of those cohorts and traces their transitions across assessments. This data was reported in a study (Kothiyal et al 2014), where in a large introductory computer science (CS101) class, learners participated in an active learning activity called Think-Pair-Share (TPS). iSAT helped to answers questions like what proportion of learners possibly benefited from the strategy as indicated by improvement in the post-test score or what proportions’ performance did not change, so possibly, they remained unaffected.Fig.…”
Interactive Stratified Attribute Tracking (iSAT) is a visual analytics tool for cohort analysis. In this paper, we show how instructors can use iSAT to visualize transitions of groups of students during teaching-learning activities. Interactive visual analytics gives the instructor the affordance of understanding the dynamics of the class of students and their activities from the data collected in their own teaching-learning context. We take an example of a peer instruction (PI) activity and describe how iSAT can be used to analyze its clicker responses. During PI, typically instructors only use histograms to visualize the distribution of clicker responses in the pre-and postdiscussion phases. We show that the use of iSAT to analyze clicker data in real time to trace transitions of participants' responses during various voting phases can support them in planning for their post-PI activities. Seven patterns of transitions that emerge are aligned, returns, starburst, slide, attractor, switching, and void. We interpret them in the context of the example. Such transition patterns are neither available in multiple histograms of individual voting phase nor generated in real time to be visualized as a flow diagram. We had conducted two workshops to introduce iSAT to the instructors and demonstrated the workflow of using iSAT with their dataset. Here, we report usefulness and usability data collected from those workshops. In conclusion, we highlight the power of iSAT for instructors to do cohort analysis in their teaching-learning practice.
“…iSAT visualizes proportions of those cohorts and traces their transitions across assessments. This data was reported in a study (Kothiyal et al 2014), where in a large introductory computer science (CS101) class, learners participated in an active learning activity called Think-Pair-Share (TPS). iSAT helped to answers questions like what proportion of learners possibly benefited from the strategy as indicated by improvement in the post-test score or what proportions’ performance did not change, so possibly, they remained unaffected.Fig.…”
Interactive Stratified Attribute Tracking (iSAT) is a visual analytics tool for cohort analysis. In this paper, we show how instructors can use iSAT to visualize transitions of groups of students during teaching-learning activities. Interactive visual analytics gives the instructor the affordance of understanding the dynamics of the class of students and their activities from the data collected in their own teaching-learning context. We take an example of a peer instruction (PI) activity and describe how iSAT can be used to analyze its clicker responses. During PI, typically instructors only use histograms to visualize the distribution of clicker responses in the pre-and postdiscussion phases. We show that the use of iSAT to analyze clicker data in real time to trace transitions of participants' responses during various voting phases can support them in planning for their post-PI activities. Seven patterns of transitions that emerge are aligned, returns, starburst, slide, attractor, switching, and void. We interpret them in the context of the example. Such transition patterns are neither available in multiple histograms of individual voting phase nor generated in real time to be visualized as a flow diagram. We had conducted two workshops to introduce iSAT to the instructors and demonstrated the workflow of using iSAT with their dataset. Here, we report usefulness and usability data collected from those workshops. In conclusion, we highlight the power of iSAT for instructors to do cohort analysis in their teaching-learning practice.
“…Think-pair-share technique more to discussion and sharing information [25]. The purpose of this technique is to encourage learners by allowing them to interact with other collaborators and sharing knowledge that leads to new information among them.…”
Web-based collaborative learning is well accepted learning methods since it provides flexibilities not only in term of learners’ interaction but also its timeliness learning materials. Even though there are many websites offer learning materials for Muslims generally but for new converted Muslims getting authentic materials and proper guidance are complicated. Hence, a web-based problem-based collaborative learning is proposed. This method integrates an elected virtual instructor to facilitate and support the new converted Muslims’ cognitive and emotional activities, develop their confidence of resolving and dealing with problems they are facing. This paper relates and analyzes the problem-based collaborative learning in terms of the functionality and user acceptance. Based on a survey conducted, it shows that 85% of the respondents found the system very useful and easy to use while 80%found that the system met their requirements. This system hypothetically able to help, and ease new converted Muslims in exploring Islamic authentic knowledge by using problem-based technique in web-based collaborative learning.
“…We generally find that preparing a Code Club session takes similar effort to preparing a Journal Club presentation. Our Code Clubs typically have 7 to 10 participants, but the inherent "think-pair-share" approach should allow it to be scaled to groups of variable sizes [13].…”
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
