scholarly journals Game-Based Learning Analytics for Supporting Adolescents’ Reflection

2021 ◽  
Vol 8 (2) ◽  
pp. 51-72
Author(s):  
Elizabeth B. Cloude ◽  
Dan Carpenter ◽  
Daryn A. Dever ◽  
Roger Azevedo ◽  
James Lester

Reflection is critical for adolescents’ problem solving and learning in game-based learning environments (GBLEs). Yet challenges exist in the literature because most studies lack a theoretical perspective and clear operational definition to inform how and when reflection should be scaffolded during game-based learning. In this paper, we address these issues by studying the quantity and quality of 120 adolescents’ written reflections and their relation to their learning and problem solving with Crystal Island, a GBLE. Specifically, we (1) define reflection and how it relates to skill and knowledge acquisition; (2) review studies examining reflection and its relation to problem solving and learning with emerging technologies; and (3) provide direction for building reflection prompts into GBLEs that are aligned with the learning goals built into the learning session (e.g., learn about microbiology versus successfully solve a problem) to maximize adolescents’ reflection, learning, and performance. Overall, our findings emphasize how important it is to examine not only the quantity of reflection but also the depth of written reflection as it relates to specific learning goals. We discuss the implications of using game-learning analytics to guide instructional decision making in the classroom.

2020 ◽  
Vol 10 (24) ◽  
pp. 9148
Author(s):  
Germán Moltó ◽  
Diana M. Naranjo ◽  
J. Damian Segrelles

Cloud computing instruction requires hands-on experience with a myriad of distributed computing services from a public cloud provider. Tracking the progress of the students, especially for online courses, requires one to automatically gather evidence and produce learning analytics in order to further determine the behavior and performance of students. With this aim, this paper describes the experience from an online course in cloud computing with Amazon Web Services on the creation of an open-source data processing tool to systematically obtain learning analytics related to the hands-on activities carried out throughout the course. These data, combined with the data obtained from the learning management system, have allowed the better characterization of the behavior of students in the course. Insights from a population of more than 420 online students through three academic years have been assessed, the dataset has been released for increased reproducibility. The results corroborate that course length has an impact on online students dropout. In addition, a gender analysis pointed out that there are no statistically significant differences in the final marks between genders, but women show an increased degree of commitment with the activities planned in the course.


1986 ◽  
Vol 59 (3) ◽  
pp. 1135-1138 ◽  
Author(s):  
Penny Armstrong ◽  
Ernest McDaniel

A computerized problem-solving task was employed to study the relationships among problem-solving behaviors and learning styles. College students made choices to find their way home in a simulated “lost in the woods” task and wrote their. reasons at each choice point. Time to read relevant information and time to make decisions were measured by the computer clock. These variables were correlated with learning style variables from Schmeck's (1977) questionnaire. The findings indicated that subjects who perceived themselves as competent learners take more time on the problem-solving task, use more information and make fewer wrong choices.


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