Instruction and Mental Model Progression: Learner‐Dependent Effects of Teaching Strategies on Knowledge Acquisition and Analogical Transfer

Seel, Norbert M.; Dinter, Frank R.

doi:10.1080/1380361950010102

Cited by 31 publications

(14 citation statements)

References 22 publications

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“…However, it is semantically sensitive toward key stimuli in the learning environment and can thus be transformed into a new model through accurate processing and interpretation of these key stimuli. The results of the experimental study of Anzai and Yokoyama (1984) as well as those of other studies (e.g., Ifenthaler, Masduki, & Seel, 2009;Ifenthaler & Seel, 2005;Seel & Dinter, 1995) demonstrate the contextual semantic sensitivity in the learning-dependent progression of mental models. Accordingly, learners search continuously for information in the given learning environment in order to complete or stabilize an initial mental model, also know as a multi-step process of model-building and revision (Penner, 2001).…”

Section: Achievement Motivationmentioning

confidence: 78%

“…Feedback on cognitive structures, such as the use of conceptual models (i.e. explicit and consistent causal explanations of a given phenomenon) to help persons to build mental models or schemata of the system being studied, has also been investigated and discussed (e.g., Mayer, 1989;Norman, 1983;Seel & Dinter, 1995). Further, new forms of automated and individualized feedback have been successfully implemented in selfregulated learning environments (e.g., Ifenthaler, 2009).…”

Section: Feedback and Cognitive Structuresmentioning

confidence: 97%

“…Accordingly, such cognitive structures are in many cases resistant to changes as they have a high subjective plausibility which requires special types of feedback. Indeed, various research studies have shown that it is very difficult but possible to influence the generation of plausible mental models by providing specific information (see Anzai & Yokoyama, 1984;Ifenthaler & Seel, 2005;Mayer, 1989;Seel, 1995;Seel & Dinter, 1995). Ifenthaler and Seel (2005) argue that it is important to consider how such feedback is provided to the learner at specific times during the learning process and how it is structured.…”

Section: Feedback and Cognitive Structuresmentioning

confidence: 98%

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A longitudinal perspective on inductive reasoning tasks. Illuminating the probability of change

Ifenthaler

Seel

2011

Learning and Instruction

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Section: Achievement Motivationmentioning

confidence: 78%

Section: Feedback and Cognitive Structuresmentioning

confidence: 97%

Section: Feedback and Cognitive Structuresmentioning

confidence: 98%

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A longitudinal perspective on inductive reasoning tasks. Illuminating the probability of change

Ifenthaler

Seel

2011

Learning and Instruction

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“…The role of mental models in deductive and inductive reasoning within learning environments has a strong theoretical foundation (see Dinter 1993;Seel 1991Seel , 2003 as well as a sound empirical basis (Al-Diban 2002;Ifenthaler 2010a;Ifenthaler and Seel 2005;Johnson et al 2009;Jonassen and Cho 2008;Jonassen et al 1997;Pirnay-Dummer and Walter 2009;Schlomske and Pirnay-Dummer 2009;Schnotz 2001;Seel and Dinter 1995). The general use of model representations in the form of concept maps for reading has already been investigated and discussed (e.g., Mayer 1989).…”

Section: Model Supported Strategies For Reading and Understandingmentioning

confidence: 98%

Reading guided by automated graphical representations: How model-based text visualizations facilitate learning in reading comprehension tasks

Pirnay-Dummer

2010

Instr Sci

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Our study integrates automated natural language-oriented assessment and analysis methodologies into feasible reading comprehension tasks. With the newly developed T-MITOCAR toolset, prose text can be automatically converted into an association net which has similarities to a concept map. The ''text to graph'' feature of the software is based on several parsing heuristics and can be used both to assess the learner's understanding by generating graphical information from his or her text and to generate conceptual graphs from text which can be used as learning materials. In this study we investigate the effects of association nets made available to learners prior to reading. The results reveal that the automatically created graphs are highly similar to classical expert graphs. However, neither the association nets nor the expert graphs had a significant effect on learning, although the latter have been reported to have an effect in previous studies.

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“…Accordingly, a central goal of our research is the investigation of the learning-dependent progression of mental models in the course of instruction. In a series of quasi-experimental studies, Seel has focused on the construction and revision of models intended for the explanation of complex phenomena as well for analogical problem solving (Seel & Dinter, 1995;Seel & Schenk, 2003;Ifenthaler & Seel, 2005;Seel, Darabi, & Nelson, 2006). Actually, a special focus in these studies was placed on measuring the stability and change of mental models in the course of learning.…”

Section: Model-oriented Instruction and Mental Model Progressionmentioning

confidence: 98%

The Role of Supportive Information in the Development and Progression of Mental Models

Darabi

Nelson

Seel

2009

Learning and Instruction in the Digital Age

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In learning a complex skill, creation and elaboration of learners' conceptual and causal models benefit from supportive information provided at the beginning of instruction. On the other hand, it has been documented that practicing problem solving leads to better performance and transfer of complex cognitive skills. Despite the essential role of problem-solving practice for integration and transfer of knowledge and skills, providing novice learners with supportive information before practice can contribute substantially to the progression of a learner's mental model toward an expert-like mental model. This progression process was examined before and after three phases of the instructional process: supportive information presentation, problem-solving practice, and test performance. Participants' mental models of the complex learning task were matched against an expert mental model at five observation points through an instructional troubleshooting session. The results indicated a significant change in participants' mental models after receiving the supportive information and no change after practice or performance. IntroductionIn this chapter, we will examine how learners build the foundation for learning in complex domains. We will discuss theoretical explanations of the interaction of supportive information and practice for the progressive development of learners' mental models. We will describe an empirical study that illustrates the importance of supportive information in the progression of mental models toward those resembling experts, and we will attempt to explain why instructional practice, though essential

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Instruction and Mental Model Progression: Learner‐Dependent Effects of Teaching Strategies on Knowledge Acquisition and Analogical Transfer

Cited by 31 publications

References 22 publications

A longitudinal perspective on inductive reasoning tasks. Illuminating the probability of change

A longitudinal perspective on inductive reasoning tasks. Illuminating the probability of change

Reading guided by automated graphical representations: How model-based text visualizations facilitate learning in reading comprehension tasks

The Role of Supportive Information in the Development and Progression of Mental Models

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