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Liu, Ou Lydia; Rios, Joseph A.; Heilman, Michael; Gerard, Libby; Linn, Marcia C. – Journal of Research in Science Teaching, 2016
Constructed response items can both measure the coherence of student ideas and serve as reflective experiences to strengthen instruction. We report on new automated scoring technologies that can reduce the cost and complexity of scoring constructed-response items. This study explored the accuracy of c-rater-ML, an automated scoring engine…
Descriptors: Science Tests, Scoring, Automation, Validity
Tansomboon, Charissa; Gerard, Libby F.; Vitale, Jonathan M.; Linn, Marcia C. – International Journal of Artificial Intelligence in Education, 2017
Supporting students to revise their written explanations in science can help students to integrate disparate ideas and develop a coherent, generative account of complex scientific topics. Using natural language processing to analyze student written work, we compare forms of automated guidance designed to motivate productive revision and help…
Descriptors: Automation, Guidance, Revision (Written Composition), Natural Language Processing
Liu, Ou Lydia; Brew, Chris; Blackmore, John; Gerard, Libby; Madhok, Jacquie; Linn, Marcia C. – Educational Measurement: Issues and Practice, 2014
Content-based automated scoring has been applied in a variety of science domains. However, many prior applications involved simplified scoring rubrics without considering rubrics representing multiple levels of understanding. This study tested a concept-based scoring tool for content-based scoring, c-raterâ„¢, for four science items with rubrics…
Descriptors: Science Tests, Test Items, Scoring, Automation
Ryoo, Kihyun; Linn, Marcia C. – Journal of Research in Science Teaching, 2016
Advances in automated scoring technologies have the potential to support student learning during inquiry instruction by providing timely and adaptive guidance on individual students' responses. To identify which forms of automated guidance can be beneficial for inquiry learning, we compared reflective guidance to directive guidance for…
Descriptors: Active Learning, Inquiry, Computer Assisted Testing, Scoring
Gerard, Libby F.; Linn, Marcia C. – Journal of Science Teacher Education, 2016
Computer scoring of student written essays about an inquiry topic can be used to diagnose student progress both to alert teachers to struggling students and to generate automated guidance. We identify promising ways for teachers to add value to automated guidance to improve student learning. Three teachers from two schools and their 386 students…
Descriptors: Scores, Automation, Essays, Classroom Techniques
Tansomboon, Charissa; Gerard, Libby F.; Vitale, Jonathan Michael; Linn, Marcia C. – AERA Online Paper Repository, 2016
While automated guidance in online units has been found to successfully support learning, students can sometimes feel alienated rather than motivated due to computerized guidance seeming impersonal. In this study, we explore ways to improve learning and motivation by personalizing adaptive guidance. Standard adaptive guidance is compared to more…
Descriptors: Web Based Instruction, Inquiry, Active Learning, Science Instruction
Vitale, Jonathan M.; Lai, Kevin; Linn, Marcia C. – Journal of Research in Science Teaching, 2015
We present a new system for automated scoring of graph construction items that address complex science concepts, feature qualitative prompts, and support a range of possible solutions. This system utilizes analysis of spatial features (e.g., slope of a line) to evaluate potential student ideas represented within graphs. Student ideas are then…
Descriptors: Scoring, Graphs, Scientific Concepts, Prompting
Gerard, Libby F.; Ryoo, Kihyun; McElhaney, Kevin W.; Liu, Ou Lydia; Rafferty, Anna N.; Linn, Marcia C. – Journal of Educational Psychology, 2016
In 4 classroom experiments we investigated uses for technologies that automatically score student generated essays, concept diagrams, and drawings in inquiry curricula. We used the automatic scores to assign typical and research-based guidance and studied the impact of the guidance on student progress. Seven teachers and their 897 students…
Descriptors: Automation, Scoring, Guidance, Inquiry