NSF Award
2417294
This project aims to serve the national interest by developing and evaluating T-PRACTISE (Team-Based Pathways and Resources to Adaptive Control Theory-Inspired Scientific Education), a team-based framework for fostering engaged online asynchronous learning among diverse students, such as adult learners. These students may be pursuing higher education asynchronously while balancing myriad work-, family-, and life-related demands in online and hybrid environments. This project addresses some of the long-standing challenges in online and hybrid learning made salient by the COVID-19 pandemic and subsequent recovery. The project plans to develop and evaluate T-PRACTISE, a set of tools that integrate current e-learning technologies with online team-based learning activities. This work aims to identify and circumvent training disparities through: (1) timely identification and delivery of remedial actions to develop pre-requisite skills; (2) an innovative algorithm to determine and provide personalized dosages of training and engagement exercises; and (3) extraction and evaluation of engagement and learning/teaching outcomes across multiple iterations and time scales to elucidate possible determinants of changes in learning/teaching and engagement outcomes.<br/><br/>This projects targets 1000 undergraduate students from online, hybrid, and in-person degree programs and is pursuing three goals. First, is to design, implement, and pilot a proof-of-concept T-PRACTISE system to reduce training and engagement disparities in an asynchronous online environment. Second, is to adapt and extend T-PRACTISE to hybrid courses with a range of environmental characteristics (e.g., student, instructor, and course). Third, is to evaluate students’ and instructors’ changes in learning/teaching outcomes, engagement, and possible moderating effects of environmental characteristics. To enhance quality control, project deliverables are refined by incorporating feedback from students, instructors, and an independent external evaluator. Efficacy of didactic activities aimed at circumventing students’ and their teams’ training disparities is evaluated based on ongoing computerized adaptive assessment results, real-time learning and engagement analytic data from T-PRACTISE and extant e-learning tools, and inclusion of students’ engagement data into the training recommendations devised by the learning algorithm in T-PRACTISE. The utility of the T-PRACTISE system will be evaluated across a variety of fully and partially online classes of different sizes for transferability and scalability. The expanded web app and resources will be made freely available to the broader research community to encourage cross-instructor, cross-departmental, and cross-institution exchanges of students’ training strategies to enhance the future of personalized and team-based higher instruction. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
