Quality Of Mental Models Research Articles

Effects of Dynamic Visualizations Enriched With Visuospatial Cues on Learners' Cognitive Load and Learning Effectiveness

The present study was to explore whether dynamic visualizations enriched with visuospatial cues can optimize learners' cognitive processing of mechanical systems. The animated conditions and cueing patterns were the independent variables with an attempt to investigate their impacts on retention and transfer tests. Either dynamic or static visualizations with the presence of visuospatial cues served as the instructional material. Two hundred thirty-eight English as a foreign language (EFL) learners participated in the experiment. The learners were distributed to six groups—either dynamic or static visualizations enriched with non-cue, entity-cues, and arrow-entity cues. Their prior knowledge was initially assessed, and then followed by retention and transfer tests and cognitive load measurements. The experimental results suggested that dynamic visualizations enriched with progressive visuospatial cues was more beneficial in helping learners to develop the favorable quality of mental models.

Principled animation design improves comprehension of complex dynamics

Learners can have difficulty in decomposing conventionally designed animations to obtain raw material suitable for building high quality mental models. A composition approach to designing animations based on the Animation Processing Model was developed as a principled alternative to prevailing approaches. Outcomes from studying novel and conventional animation designs (independent variable) were compared with respect to mental model quality, knowledge of local kinematics, and capacity to transfer (dependent variables). Study of a compositional animation that presented material in a contiguous fashion resulted in higher quality mental models of a piano mechanism than non-contiguous or control (conventional) versions but no significant differences regarding local kinematics or transfer. Eye fixation data indicated that the compositional animation led to superior mental models because it particularly fostered relational processing. Implications for future research and the design of educational animations are discussed.

Managing information overload in virtual teams: Effects of a structured online team adaptation on cognition and performance

Information overload (IO) indicates the exchange of too much low-quality information in virtual teams. When being overloaded with information, teams need to adapt and to change communication behaviour. This study introduces and tests a structured online team adaptation (STROTA) procedure that enables virtual teams to reduce IO by improving their team mental model quality. STROTA, built from team adaptation models, is a moderated intervention consisting of three stages: (1) individual situation awareness, (2) team situation awareness, and (3) plan formulation. STROTA was tested in the context of an experimental problem-solving task. Participants (N = 363) worked in virtual teams of three and were randomly assigned to one of four experimental conditions: no STROTA, incomplete STROTA (step 1, steps 1–2), and complete STROTA (steps 1–2–3). We found teams that followed a complete STROTA procedure experienced lessened IO over time. Teams with complete STROTA showed the largest development of TMM immediately after STROTA. Finally, multilevel mediation analyses showed that TMM are mediators that explain the influence of STROTA on IO.

Importance of Computer Assisted Teaching & Learning Methods for Chemistry

Understanding the basic concepts of chemistry is very important for the students of secondary school level and university level. The Computer Assisted Teaching and Learning (CATL) methods are marked by the usage of computers in teaching and learning processes. Usage of WORD, EXCEL, POWERPOINT, ACCESS, PHOTOSHOP etc., as well as the use of specialized packages such as CHEMDRAW, SCIFINDER etc., can be worth mentioning. The role of internet in feeding the thirst of students is comparably far better than the classroom teaching. By the use of CATL methods, students can acquire high quality of mental models.

Investigating the quality of mental models deployed by undergraduate engineering students in creating explanations: The case of thermally activated phenomena

This paper describes a method aimed at pointing out the quality of the mental models undergraduate engineering students deploy when asked to create explanations for phenomena or processes and/or use a given model in the same context. Student responses to a specially designed written questionnaire are quantitatively analyzed using researcher-generated categories of reasoning, based on the physics education research literature on student understanding of the relevant physics content. The use of statistical implicative analysis tools allows us to successfully identify clusters of students with respect to the similarity to the reasoning categories, defined as ``practical or everyday,'' ``descriptive,'' or ``explicative.'' Through the use of similarity and implication indexes our method also enables us to study the consistency in students' deployment of mental models. A qualitative analysis of interviews conducted with students after they had completed the questionnaire is used to clarify some aspects which emerged from the quantitative analysis and validate the results obtained. Some implications of this joint use of quantitative and qualitative analysis for the design of a learning environment focused on the understanding of some aspects of the world at the level of causation and mechanisms of functioning are discussed.

Cueing animations: Dynamic signaling aids information extraction and comprehension

The effectiveness of animations containing two novel forms of animation cueing that target relations between event units rather than individual entities was compared with that of animations containing conventional entity-based cueing or no cues. These relational event unit cues (progressive path and local coordinated cues) were specifically designed to support key learning processes posited by the Animation Processing Model (Lowe & Boucheix, 2008). Four groups of undergraduates (N = 84) studied a user-controllable animation of a piano mechanism and then were assessed for mental model quality (via a written comprehension test) and knowledge of the mechanism's dynamics (via a novel non-verbal manipulation test). Time-locked eye tracking was used to characterize participants' obedience to cues (initial engagement versus ongoing loyalty) across the learning period. For both output measures, participants in the two relational event unit cueing conditions were superior to those in the entity-based and uncued conditions. Time-locked eye tracking analysis of cue obedience revealed that initial cue engagement did not guarantee ongoing cue loyalty. The findings suggest that the Animation Processing Model provides a principled basis for designing more effective animation support.

“The More You Gesture, the Less I Gesture”: Co-Speech Gestures as a Measure of Mental Model Quality

Studies in the literature have revealed that a speaker’s co-speech gestures favor the construction of a complete and articulated mental model of the discourse by the listener; moreover, from the literature on co-speech gestures we know that they help the speaker to organize the stream of thought. Given these data, we hypothesized that a person who listens to a discourse accompanied by gestures would produce fewer co-speech gestures in recollecting the discourse compared to a person who listens to a discourse not accompanied by gestures. The analysis of the co-speech gestures produced by the participants in two experiments while recollecting the content of a discourse confirmed our predictions.

Mental model metrics and team adaptability: A multi-facet multi-method examination.

This paper empirically examines the convergent, discriminant, and predictive validity of three team mental model measurement approaches. Specifically, this study measures the similarity (MM-similarity) and quality (MM-quality) facets of team strategyfocused mental models using structural networks, priority rankings, and importance ratings. The convergent and divergent relationships among the three mental model metrics are then examined via a multi-facet multi-method matrix. Finally, the relative utility of each metric for understanding the relationships between team mental models, team adaptability, and decision effectiveness are compared. The study was conducted in a laboratory setting, modeling 56 four-person decision-making teams. Results indicate little convergent and extensive discriminant validity across the three mental model metrics. In addition, only mental models measured using the structural networks metric were found to have predictive validity in relation to team adaptation and performance. The quality and similarity of team structural networks were found to have interactive effects in relation to adaptation such that mental model quality was most strongly related to adaptation for teams with low mental model similarity and unrelated to adaptation for teams with high similarity. In turn, adaptation was critical for team decision effectiveness.

Effects of Mental Model Quality on Collaborative System Performance

This ongoing study is exploring how varying levels of user mental model quality influence performance with an imperfect automated system (navigational aid). The number and types of errors produced by participants is of particular interest along with how mental models influence user trust and reliance with automation. The design attempts to manipulate the acquisition of mental models by varying exposure to the task environment between groups. A high acquisition group, low acquisition group, and no acquisition group navigated the confines of a simulated city with the help of an automated aid performing at two levels of reliability. Implications of this study could influence the design of automated systems and their associated user training programs. Additionally, this study could spur additional research into the effects of mental model quality on automated system performance.

Scaling the quality of teammates' mental models: equifinality and normative comparisons

We tested the impact of teammates' team and task mental model sharedness on team processes and performance using 70 undergraduate teams that completed a series of missions on a PC-based flight simulator. Moreover, we considered how the quality of mental models might moderate such relationships. Team processes were found to partially mediate the relationship between task mental model sharedness and team performance. Although team mental model sharedness failed to exhibit a significant linear relationship with team processes or performance, it did evidence a multiplicative relationship as moderated by the quality of those models. Team processes and performance were better among teams sharing higher-quality team mental models than among teams evidencing less sharedness or who had lower-quality models. Again, team processes partially mediated these relationships. Results are discussed in terms of the equifinality of mental model quality and applications to various team environments. Copyright © 2005 John Wiley & Sons, Ltd.