Model-Based Learning and Performance

Seel, Norbert M.

doi:10.1007/978-1-4614-3185-5_37

Cited by 16 publications

(7 citation statements)

References 86 publications

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“…Over the last decades, there has been significant interest in using computer modelling tools to support students' learning of science (Khine & Saleh, 2011;Seel, 2014). Computer models and model-based reasoning have been seen as potentially beneficial for learning complex scientific knowledge for several reasons.…”

Section: Leaning With Computer Modelsmentioning

confidence: 99%

Measuring and Visualizing Learning in the Information-Rich Classroom

Reimann

Bull²,

Kickmeier-Rust

et al. 2015

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Integrated information systems are increasingly used in schools, and the advent of the technology-rich classroom requires a new degree of ongoing classroom assessment. Able to track web searches, resources used, task completion time, and a variety of other classroom behaviors, technology-rich classrooms offer a wealth of potential information about teaching and learning. This information can be used to track student progress in languages, STEM, and in 21st Century skills, for instance. However, despite these changes, there has been little change in the kind of data made available to teachers, administrators, students, and parents.Measuring and Visualizing Learning in the Information-Rich Classroom collects research on the implementation of classroom assessment techniques in technology-enhanced learning environments. Building on research conducted by a multinational and multidisciplinary team of learning technology experts, and specialists from around the globe, this book addresses these discrepancies. With contributions from major researchers in education technology, testing and assessment, and education psychology, this book contributes to a holistic approach for building the information infrastructure of the 21st Century school.

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Section: Leaning With Computer Modelsmentioning

confidence: 99%

Measuring and Visualizing Learning in the Information-Rich Classroom

Reimann

Bull²,

Kickmeier-Rust

et al. 2015

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“…Changing behavior obtained from knowledge or skills is the main goal of studying mathematics. Learning mathematics teaches many things and emphasizes many aspects such as communication (Sfard, 2001;Tabach & Nachlieli, 2016); quantity, space, and structure (Seel, 2014); computing, and problem-solving skills (Yeh et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

The impact of affective skills toward on the mathematics learning outcomes at senior high school students

Wahyuddin

Rusdin

Nur³

2022

jel

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Affective skill is one of the factors that students must possess and are the key to successful learning; affective skills are also one of the skills needed in the world of work in the future. This research aimed to analyze the influence of affective skills and their influence on learning outcomes and the dominant influencing variables. This quantitative survey was conducted in January-March 2021, involving 155 students (61 males and 94 females). The variables consisted of exogenous variables, namely affective skills (math interest, math anxiety, math self-efficacy, beliefs, and math attitude), while endogenous variables are learning outcomes. The instrument used to measure exogenous variables were questionnaires including math interest, math anxiety, math self-efficacy, beliefs, and math attitude that met the validity and reliability tests. While the endogenous variable, namely understanding results obtained from the value of documentation of student learning outcomes at school. The data was processed by descriptive and inferential analysis through structural equation modeling (SEM). The study results concluded that math self-efficacy and math attitude were in the high category, beliefs and math interests were suitable. Math anxiety was of a low sort. Furthermore, math interest, math self-efficacy, beliefs, and math attitude were found to have no significant effect on learning outcomes, which means that math interest, self-efficacy, ideas, and math attitude were not sufficient to provide evidence that they could significantly influence learning outcomes.

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“…Because of the importance of models and modeling in mathematics and science (education), several model-centered approaches of learning and instruction, have been developed since the very beginning of the 1970s and are still promising today. Actually, two broad areas of model-centered instruction have been around for more than 40 years: One of them is based on pragmatics – and goes “beyond constructivism” (Lesh and Doerr 2003; Stachowiak 1973), while the other is largely inspired by the theory of mental models and goes “beyond pragmatism” (see, for more information, Seel 2009b). …”

Section: Introductionmentioning

confidence: 99%

“…This research on subject matter-oriented model-centered learning has been related often, but not exclusively, to qualitative research methods, such as collecting verbal data from think-aloud protocols, observational data, and videotape analyses. In addition, some researchers feel obliged to do design-based research and consider model-building in the classroom as a testing ground for design experiments (Seel 2009b). Design experiments aim at particular forms of educational interventions that create novel conditions for learning and instruction (Brown 1992; Lehrer et al 2007).…”

Section: Introductionmentioning

confidence: 99%

General Didactics and Instructional Design: eyes like twins A transatlantic dialogue about similarities and differences, about the past and the future of two sciences of learning and teaching

Zierer

Seel

2012

SpringerPlus

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Although General Didactics (GD) and Instructional Design (ID) have not shown many points of contact in the past, there are some obvious parellels from the perspective of their historical development. This will be examined in detail in this article. More specifically, we speak about model building, which has characterized General Didactics and Instructional Design for some decades. However, the models of General Didactics and Instructional Design are not problem-free with regard to the continuity and advancement of both disciplines. First, we will describe the historical roots of both disciplines and examine which elements of theory are of central importance. Second, we will try to answer the question of which kind of model building could be considered as predominant and what problems result from this predominance. In order to do this, we will describe empirical studies on the use of instructional models and discuss these studies from the perspective of the philosophy of science. Third, we will draw inferences for future processes of model building in order to prevent the same problems that happened in the past from happening again. Finally, we will discuss the issue of what General Didactics can learn from Instructional Design and vice versa.

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Model-Based Learning and Performance

Cited by 16 publications

References 86 publications

Measuring and Visualizing Learning in the Information-Rich Classroom

Measuring and Visualizing Learning in the Information-Rich Classroom

The impact of affective skills toward on the mathematics learning outcomes at senior high school students

General Didactics and Instructional Design: eyes like twins A transatlantic dialogue about similarities and differences, about the past and the future of two sciences of learning and teaching

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