Collaborative group engagement in a computer-supported inquiry learning environment

Computer-supported collaborative learning environments provide opportunities for students to collaborate in inquiry-based practices to solve authentic problems, using technological tools as a resource. However, we have limited understanding of the quality of engagement fostered in these contexts, in part due to the narrowness of engagement measures. To help judge the quality of engagement, we extend existing engagement frameworks, which have studied this construct as a stable and decontextualized individual difference. We conceptualize engagement as multi-faceted (including behavioral, social, cognitive and conceptual-toconsequential forms), dynamic, contextualized and collective. Using our newly developed observational measure, we examine the variation of engagement quality for ten groups. Subsequently, we differentiate low and high quality collaborative engagement through a close qualitative analysis of two groups. Here, we explore the interrelationships among engagement facets and how these relations unfolded over the course of group activity during a lesson. Our results suggest that the quality of behavioral and social engagement differentiated groups demonstrating low quality engagement, but cognitive and conceptual-to-consequential forms are required for explaining high quality engagement. Examination of interrelations indicate that behavioral and social engagement fostered high quality cognitive engagement, which then facilitated consequential engagement. Here, engagement is evidenced as highly interrelated and mutually influencing interactions among all four engagement facets. These findings indicate the benefits of studying engagement as a multi-faceted phenomenon and extending existing conceptions to include consequential engagement, with implications for designing technologies that scaffold high quality cognitive and conceptual-to-consequential engagement in a computer-supported collaborative learning environment. Intern. J. Comput.-Support. Collab. Learn (2015) 10:273–307 DOI 10.1007/s11412-015-9218-y * Suparna Sinha [email protected] 1 Center for Math, Science & Computer Education, Rutgers University, 118 Frelinghuysen Road, Piscataway, NJ 08854, USA 2 Purdue University, West Lafayette, IN, USA 3 Indiana University, Bloomington, IN, USA