Interdisciplinary research agenda in support of assessment of collaborative problem solving: lessons learned from developing a Collaborative Science Assessment Prototype

Abstract Evidence from labor-market economics and predictive validity studies in psychology suggests that collaborative problem solving (CPS) is an increasingly important skill for both academic and career success in the 21st century. While there is a general agreement that collaborative problem solving is an important skill, there is less agreement on how to build an assessment to measure it, especially at scale and as a standardized test. Developing the type of CPS assessment envisioned in this work will require interdisciplinary synergy, involving learning science, data science, psychometrics, and software engineering. In this conceptual paper, we present our identification and novel instantiation of five interdisciplinary research strands supporting the development of a CPS assessment. We discuss how these research strands can comprehensively address some of the shortcomings of existing CPS assessments, such as collecting and managing the data from the process of collaboration in structured log files, or considering a statistical definition of collaboration in the design of the collaborative tasks. We describe the Collaborative Science Assessment Prototype developed at Educational Testing Service (ETS) under the proposed interdisciplinary research agenda to illustrate how these research strands can be operationalized.

[1]  Lei Liu,et al.  Collaborative Problem Solving Skills versus Collaboration Outcomes: Findings from Statistical Analysis and Data Mining , 2016, EDM.

[2]  Lei Liu,et al.  A Tough Nut to Crack: Measuring Collaborative Problem Solving , 2016 .

[3]  Leslie A. DeChurch,et al.  The cognitive underpinnings of effective teamwork: a meta-analysis. , 2010, The Journal of applied psychology.

[4]  Lei Liu,et al.  Measuring Student Engagement during Collaboration. , 2017 .

[5]  Erik Lindqvist,et al.  The Labor Market Returns to Cognitive and Noncognitive Ability: Evidence from the Swedish Enlistment , 2009 .

[6]  Hanna Järvenoja,et al.  Research on Motivation in Collaborative Learning: Moving Beyond the Cognitive–Situative Divide and Combining Individual and Social Processes , 2010 .

[7]  Brigid Barron When Smart Groups Fail , 2003 .

[8]  Yuen-Hsien Tseng,et al.  Are you SLiM? Developing an instrument for civic scientific literacy measurement (SLiM) based on media coverage , 2012, Public understanding of science.

[9]  Harold F. O'Neil,et al.  Workforce Readiness: Competencies and Assessment. , 1997 .

[10]  Peter F. Halpin,et al.  Modelling Dyadic Interaction with Hawkes Processes , 2013, Psychometrika.

[11]  Kurt VanLehn Intelligent Tutoring Systems for Continuous, Embedded Assessment , 2007 .

[12]  Patrick Griffin,et al.  The Changing Role of Education and Schools , 2012 .

[13]  D. Meyer,et al.  Supporting Online Material Materials and Methods Som Text Figs. S1 to S6 References Evidence for a Collective Intelligence Factor in the Performance of Human Groups , 2022 .

[14]  Pierre Dillenbourg,et al.  The Evolution of Research on Computer-Supported Collaborative Learning , 2009 .

[15]  Peter F. Halpin,et al.  Modeling Collaboration Using Point Processes , 2017 .

[16]  Robert J. Mislevy,et al.  Taming Log Files From Game/Simulation‐Based Assessments: Data Models and Data Analysis Tools , 2016 .

[17]  Andrew B. Hargadon,et al.  Brainstorming groups in context: Effectiveness in a product design firm , 1996 .

[18]  P. Kirschner,et al.  Social and Cognitive Factors Driving Teamwork in Collaborative Learning Environments , 2006 .

[19]  Friedrich W. Hesse,et al.  A Framework for Teachable Collaborative Problem Solving Skills , 2015 .

[20]  Ronald H. Stevens,et al.  Applications of Stochastic Analyses for Collaborative Learning and Cognitive Assessment , 2007 .

[21]  Lei Liu,et al.  Modeling Collaborative Interaction Patterns in a Simulation‐Based Task , 2017 .

[22]  Peter W. Foltz,et al.  Assessing Collaborative Problem Solving Through Automated Technologies , 2014 .

[23]  Russell G. Almond,et al.  You Can't Fatten A Hog by Weighing It - Or Can You? Evaluating an Assessment for Learning System Called ACED , 2008, Int. J. Artif. Intell. Educ..

[24]  Jiangang Hao,et al.  EPCAL: ETS Platform for Collaborative Assessment and Learning , 2017 .

[25]  M. Kane Validating the Interpretations and Uses of Test Scores , 2013 .

[26]  María José del Jesús,et al.  Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data , 2009, Expert Syst. Appl..

[27]  John R. Anderson,et al.  Knowledge tracing: Modeling the acquisition of procedural knowledge , 2005, User Modeling and User-Adapted Interaction.

[28]  Peter F. Halpin,et al.  Collaborative Problem Solving and the Assessment of Cognitive Skills: Psychometric Considerations. Research Report. ETS RR-13-41. , 2013 .

[29]  Mengxiao Zhu,et al.  Innovative Assessment of Collaboration , 2017 .

[30]  Lei Liu,et al.  Assessing Collaborative Problem Solving with Simulation Based Tasks , 2015, CSCL.

[31]  R. A. Leibler,et al.  On Information and Sufficiency , 1951 .

[32]  Jessica J. Andrews,et al.  Benefits, Costs, and Challenges of Collaboration for Learning and Memory , 2015 .

[33]  S. Gosling,et al.  A very brief measure of the Big-Five personality domains , 2003 .

[34]  Michel C. Desmarais,et al.  A review of recent advances in learner and skill modeling in intelligent learning environments , 2012, User Modeling and User-Adapted Interaction.

[35]  Aniket Kittur,et al.  Crowdsourcing user studies with Mechanical Turk , 2008, CHI.

[36]  Jeremy Burrus,et al.  IDENTIFYING THE MOST IMPORTANT 21ST CENTURY WORKFORCE COMPETENCIES: AN ANALYSIS OF THE OCCUPATIONAL INFORMATION NETWORK (O*NET) , 2013 .

[37]  Lei Liu,et al.  Assessing Science Inquiry Skills Using Trialogues , 2014, Intelligent Tutoring Systems.

[38]  Rachel A. Lotan,et al.  Complex instruction: Equity in cooperative learning classrooms , 1999 .

[39]  Lei Liu,et al.  On Convergence of Cognitive and Non-cognitive Behavior in Collaborative Activity , 2015, EDM.

[40]  Alina A. von Davier,et al.  Computational Psychometrics in Support of Collaborative Educational Assessments , 2017 .

[41]  N. Rummel,et al.  Learning to Collaborate: An Instructional Approach to Promoting Collaborative Problem Solving in Computer-Mediated Settings , 2005 .

[42]  Lei Liu,et al.  Automated classification of collaborative problem solving interactions in simulated science tasks , 2016, BEA@NAACL-HLT.