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Your search keyword '"Scheiter, Katharina"' showing total 3 results
Start Over Author "Scheiter, Katharina" Publication Type Reports
3 results on '"Scheiter, Katharina"'

1. Development and validation of the Converging Lenses Concept Inventory for middle school physics education

Author

Wörner, Salome, Becker, Sebastian, Küchemann, Stefan, Scheiter, Katharina, and Kuhn, Jochen

Subjects
Physics - Physics Education
Abstract

Optics is a core field in the curricula of secondary physics education. In this study, we present the development and validation of a test instrument in the field of optics, the Converging Lenses Concept Inventory (CLCI). It can be used as a formative or a summative assessment of middle school students' conceptual understanding of image formation by converging lenses. The CLCI assesses: (1) the overall understanding of fundamental concepts related to converging lenses, (2) the understanding of specific concepts, and (3) students' propensity for difficulties within this topic. The initial CLCI consists of 16 multiple-choice items; however, one item was removed based on various quality checks. We validated the CLCI thoroughly with distractor analyses, classical test theory, item response theory, structural analyses, and analyses of students' total scores at different measurement points as quantitative approaches, as well as student interviews and an expert survey as qualitative approaches. The quantitative analyses are mostly based on a dataset of N = 318 middle school students who took the CLCI as a posttest. The student interviews were conducted with seven middle school students after they were taught the concepts of converging lenses. The expert survey included five experts who evaluated both individual items and the test as a whole. The analyses showed good to excellent results for the test instrument, corroborating the 15-item CLCI's validity and its compliance with the three foci outlined above.

Published
2022

2. Let's Talk Evidence--The Case for Combining Inquiry-Based and Direct Instruction

Author

de Jong, Ton, Lazonder, Ard W., Chinn, Clark A., Fisher, Frank, Gobert, Janice, Hmelo-Silver, Cindy E., Koedinger, Ken R., Krajcik, Joseph S., Kyza, Eleni A., Linn, Marcia C., Pedaste, Margus, Scheiter, Katharina, and Zacharia, Zacharias C.

Abstract

Many studies investigating inquiry learning in science domains have appeared over the years. Throughout this period, inquiry learning has been regularly criticized by scholars who favor direct instruction over inquiry learning. In this vein, Zhang, Kirschner, Cobern, and Sweller (2022) recently asserted that direct instruction is overall superior to inquiry-based instruction and reproached policy makers for ignoring this fact. In the current article we reply to this assertion and the premises on which it is based. We review the evidence and argue that a more complete and correct interpretation of the literature demonstrates that inquiry-based instruction produces better overall results for acquiring conceptual knowledge than does direct instruction. We show that this conclusion holds for controlled, correlational, and program-based studies. We subsequently argue that inquiry-based and direct instruction each have their specific virtues and disadvantages and that the effectiveness of each approach depends on moderating factors such as the learning goal, the domain involved, and students' prior knowledge and other student characteristics. Furthermore, inquiry-based instruction is most effective when supplemented with guidance that can be personalized based on these moderating factors and can even involve providing direct instruction. Therefore, we posit that a combination of inquiry and direct instruction may often be the best approach to support student learning. We conclude that policy makers rightfully advocate inquiry-based instruction, particularly when students' investigations are supplemented with direct instruction at appropriate junctures.

Published
2023
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3. Deep semantic gaze embedding and scanpath comparison for expertise classification during OPT viewing

Author

Castner, Nora, Kübler, Thomas, Scheiter, Katharina, Richter, Juilane, Eder, Thérése, Hüttig, Fabian, Keutel, Constanze, and Kasneci, Enkelejda

Subjects
Computer Science - Machine Learning, Computer Science - Human-Computer Interaction, Statistics - Machine Learning
Abstract

Modeling eye movement indicative of expertise behavior is decisive in user evaluation. However, it is indisputable that task semantics affect gaze behavior. We present a novel approach to gaze scanpath comparison that incorporates convolutional neural networks (CNN) to process scene information at the fixation level. Image patches linked to respective fixations are used as input for a CNN and the resulting feature vectors provide the temporal and spatial gaze information necessary for scanpath similarity comparison.We evaluated our proposed approach on gaze data from expert and novice dentists interpreting dental radiographs using a local alignment similarity score. Our approach was capable of distinguishing experts from novices with 93% accuracy while incorporating the image semantics. Moreover, our scanpath comparison using image patch features has the potential to incorporate task semantics from a variety of tasks

Published
2020

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