Nani Teig|Ronny Scherer|Marit Kjærnsli
Identifying patterns of students' performance on simulated inquiry tasks using <scp>PISA</scp> 2015 log?file data
University of Oslo|University of Oslo|University of Oslo
abstract previous research demonstrated potential examining logfile data computerbased assessments understand student interactions complex inquiry tasks rather solely providing information achieved accuracy student responses product data students log files offer additional insights responses produced process data study examined students log files detect patterns students interactions computerbased assessment determine whether unique characteristics interactions emerge distinct profiles inquiry performance knowledge characteristics profiles shed light students successful solving simulated inquiry tasks others support student understanding scientific inquiry computerbased environments analyzed norwegian pisa 2015 logfile data science performance well background questionnaire n 1222 students focusing two inquiry tasks required scientific reasoning skills coordinating effects multiple variables coordinating theory evidence using mixture modeling approach identified three distinct profiles students inquiry performance strategic emergent disengaged profiles revealed different characteristics students exploration behavior inquiry strategy timeontask item accuracy analyses showed students assignment profiles varied according demographic characteristics gender socioeconomic status language home attitudes enjoyment science selfefficacy test anxiety science achievement although students profiles two inquiry tasks significantly related also found variations proportion students transitions profiles study contributes understanding students interact complex simulated inquiry tasks showcases logfile data pisa 2015 aid understanding