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1. Concept-Level Design Analytics for Blended Courses

   https://doi.org/10.1007/978-3-030-29736-7_40  

   Albó, Laia; Barria-Pineda, Jordan; Brusilovsky, Peter; Hernández-Leo, Davinia (September 2019, Proceedings of 14th European Conference on Technology Enhanced Learning (EC-TEL 2019))

   Although many efforts are being made to provide educators with dashboards and tools to understand student behaviors within specific technological environments (learning analytics), there is a lack of work in supporting educators in making data-informed design decisions when designing a blended course and planning learning activities. In this paper, we introduce concept-level design analytics, a knowledge-based visualization, which uncovers facets of the learning activities that are being authored. The visualization is integrated into a (blended) learning design authoring tool, edCrumble. This new approach is explored in the context of a higher education programming course, where teaching assistants design labs and home practice sessions with online smart learning content on a weekly basis. We performed a within-subjects user study to compare the use of the design tool both with and without the visualization. We studied the differences in terms of cognitive load, design outcomes and user actions within the system to compare both conditions to the objective of evaluating the impact of using design analytics during the decision-making phase of course design. 

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2. How Teachers From Underrepresented Schools Experienced a Blended Professional Development Program on Computer Science and Game Design

   Dogan, S; Akcaoglu, M (November 2023, Teacher education quarterly)

   Learning computer science (CS) is increasingly becoming a necessary component of K–12 education, but in most cases, teachers do not have either the essential knowledge to teach or a curriculum to follow. In this article, we analyze the outcomes from a yearlong, blended professional development (PD) program to teach teachers game design and coding skills, and we codevelop a middle school curriculum. Using a mixed-methods design, this study presents the findings as we investigate how teachers experienced the PD program. Our findings show that the teachers’ level of engagement differed for various reasons, such as challenges related to time, motivation, and interest. We identified a high-engagement group who developed a deep understanding of coding knowledge and engaged in the PD activities more. We also identified a low-engagement group who failed to attend most activities despite mentioning generic interests. We provide an explanation why these teachers might have varied in terms of their engagement and offer how “data” can be used to predict engagement levels and as a diagnostic tool (e.g., lacked specificity in explaining CS concepts in reflections). We recommend add- ing motivational strategies and better tracking and monitoring mechanisms for better engagement and PD design considerations for online and blended learning for teachers. 

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3. Design and Usability Evaluation of an End User Programming Environment for Equipping Construction Students with Sensor Data Analytics Skills

   https://doi.org/10.36680/j.itcon.2025.010  

   Khalid, Mohammad; Akanmu, Abiola; Afolabi, Adedeji; Murzi, Homero; Awolusi, Ibukun; Agee, Philip (January 2025, Journal of Information Technology in Construction)

   Classification of construction resource states, using sensor data analytics, has implications for improving informed decision-making for safety and productivity. However, training on sensor data analytics in construction education faces challenges owing to the complexity of analytical processes and the large stream of raw data involved. This research presents the development and user evaluation of ActionSens, a block-based end-user programming platform, for training students from construction-related disciplines to classify resources using sensor data analytics. ActionSens was designed for construction students to perform sensor data analytics such as activity recognition in construction. ActionSens was compared to traditional tools (i.e., combining Excel and MATLAB) used for performing sensor data analytics in terms of usability, workload, visual attention, and processing time using the System Usability Scale, NASA Task Load Index, eye-tracking, and qualitative feedback. Twenty students participated, performing data analytics tasks with both approaches. ActionSens exhibited a better user experience compared to conventional platforms, through higher usability scores and lower cognitive workload. This was evident through participants' interaction behavior, showcasing optimized attentional resource allocation across key tasks. The study contributes to knowledge by illustrating how the integration of construction domain information into block-based programming environments can equip students with the necessary skills for sensor data analytics. The development of ActionSens contributes to the Learning-for-Use framework by employing graphical and interactive programming objects to foster procedural knowledge for addressing challenges in sensor data analytics. The formative evaluation provides insights into how students engage with the programming environment and assesses the impact of the environment on their cognitive load. 

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4. Supporting Teachers to Customize Curriculum for Self-Directed Learning

   https://doi.org/10.1007/s10956-022-09985-w  

   Gerard, Libby; Bradford, Allison; Linn, Marcia C. (August 2022, Journal of Science Education and Technology)

   Abstract Guiding teachers to customize curriculum has shown to improve science instruction when guided effectively. We explore how teachers use student data to customize a web-based science unit on plate tectonics. We study the implications for teacher learning along with the impact on student self-directed learning. During a professional development workshop, four 7th grade teachers reviewed logs of their students’ explanations and revisions. They used a curriculum visualization tool that revealed the pedagogy behind the unit to plan their customizations. To promote self-directed learning, the teachers decided to customize the guidance for explanation revision by giving students a choice among guidance options. They took advantage of the web-based unit to randomly assign students (N = 479) to either a guidance Choice or a no-choice condition. We analyzed logged student explanation revisions on embedded and pre-test/post-test assessments and teacher and student written reflections and interviews. Students in the guidance Choice condition reported that the guidance was more useful than those in the no-choice condition and made more progress on their revisions. Teachers valued the opportunity to review student work, use the visualization tool to align their customization with the knowledge integration pedagogy, and investigate the choice option empirically. These findings suggest that the teachers’ decision to offer choice among guidance options promoted aspects of self-directed learning. 

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5. Preparing Pre-Service Teacher Candidates for the Praxis Exam: An Innovative Model of Blended Support

   https://doi.org/10.1145/3328778.3372654  

   Odom-Bartel, Rebecca; Fletcher, Carol; Owen, John; Gray, Jeff; Zelkowski, Jeremy (February 2020, ACM Technical Symposium on Computer Science Education (SIGSCE))

   null (Ed.)

   The expansion of K-12 computer science (CS) has driven a dramatic need for educators who are trained in CS content and pedagogy [1]. This poster describes our effort to train teacher candidates (i.e., pre-service teachers who are students seeking degrees within a College of Education), who are specializing in secondary mathematics education, to be future CS educators. We specifically describe our collaboration to provide a blended preparatory six-week training for the ETS CS Praxis exam (5652), assisting our pre-service students in satisfying the CS certification requirements in our state before they graduate and begin their professional teaching career. Given the unique challenges of pre-service CS teacher preparation [2], blended models, which combine both in-person and online instruction, are an effective approach to building a pre-service program. Within our pre-service CS program, students first complete a two-course pathway that prepares them in AP CSP content and pedagogy experiences, including observations in local AP CSP classrooms [3]. After completing the two courses, our students participate in the blended version of the WeTeach_CS Praxis preparation course to achieve certification. The in-person support provided by the blended model contributed significantly to certification success in this project. With a cut-score of 149 for the Praxis exam, all 11 of our pre-service students who completed the course received a passing score (including one student with a perfect score of 200, and another student with a 195); the average score for our pre-service students was 175. An additional 11 in-service teachers, with diverse backgrounds in CS content knowledge, also participated in the blended Praxis preparation course, with an average score of 166. Given the unique challenges of pre-service CS teacher preparation, university pre-service CS teacher programs should look to innovative models of teacher support developed by in-service programs to make substantial gains in CS teacher certification. Incorporating an asynchronous online course that allows teachers with a wide range of prior experience in CS to learn at their own pace with in-person coursework and support appears to be a viable model for assisting non-CS major teacher candidates in achieving a CS certification. With the blended model, even teachers with no background knowledge in CS were successful. Within our pre-service CS program, students first complete a two-course pathway that prepares them in AP CSP content and pedagogy experiences, including observations in local AP CSP classrooms [3]. After completing the two courses, our students participate in the blended version of the WeTeach_CS Praxis preparation course to achieve certification. The in-person support provided by the blended model contributed significantly to certification success in this project. With a cut-score of 149 for the Praxis exam, all 11 of our pre-service students who completed the course received a passing score (including one student with a perfect score of 200, and another student with a 195); the average score for our pre-service students was 175. An additional 11 in-service teachers, with diverse backgrounds in CS content knowledge, also participated in the blended Praxis preparation course, with an average score of 166. Incorporating an asynchronous online course that allows teachers with a wide range of prior experience in CS to learn at their own pace with in-person coursework and support appears to be a viable model for assisting non-CS major teacher candidates in achieving a CS certification. With the blended model, even teachers with no background knowledge in CS were successful. 

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