The relation between the intelligibility of irrelevant speech and cognitive performance—A revised model based on laboratory studies

Indoor Air ◽  
2020 ◽  
Vol 30 (6) ◽  
pp. 1130-1146
Author(s):  
Annu Haapakangas ◽  
Valtteri Hongisto ◽  
Andreas Liebl
Keyword(s):  
Cognitive Performance ◽  
Irrelevant Speech ◽  
Laboratory Studies ◽  
Model Based

Empirical Research on Populations of Adaptive Individuals

2020 ◽  
pp. 141-153
Keyword(s):  
Empirical Research ◽  
Empirical Studies ◽  
Theory Development ◽  
Organization Change ◽  
Laboratory Studies ◽  
Design Studies ◽  
Entire Process ◽  
Levels Of Organization ◽  
Model Based ◽  
Multiple Levels

This chapter studies how modeling supports empirical research. The benefit of integrating modeling and empirical research has long been recognized: theorists and modelers pose hypotheses that empirical researchers then design studies to test, and empirical research informs the development of new hypotheses. Such integration may be particularly valuable in frameworks that include multiple levels of organization, from individuals to populations to communities. But does working across levels of organization change the relationships of theory, modeling, and empirical research? What kinds of field and laboratory studies do we need, and at what levels of organization, to support modeling? The chapter assesses these questions. Thinking about the relation between modeling and empirical research requires one to address the entire process of model-based research, which is usefully characterized as a modeling cycle. The chapter then explores how the kind of modeling and theory development presented in this book can contribute to empirical studies and research.

A model-based solution for observational errors in laboratory studies

2018 ◽  
Vol 18 (3) ◽  
pp. 580-589 ◽  
Author(s):  
Brian M. Brost ◽  
Brittany A. Mosher ◽  
Kristen A. Davenport
Keyword(s):  
Laboratory Studies ◽  
Model Based ◽  
Observational Errors

scholarly journals MODEL-BASED CLUSTER ANALYSES OF COGNITION FOR UNPACKING SUBGROUP DIFFERENCES IN PSYCHOSOCIAL OUTCOMES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S810-S810
Author(s):  
Nelson A Roque ◽  
Martin J Sliwinski
Keyword(s):  
Cognitive Performance ◽  
Methodological Approach ◽  
Community Dwelling ◽  
Cluster Solution ◽  
Physical And Mental Health ◽  
Cluster Analyses ◽  
Stress Memory ◽  
Memory Complaints ◽  
Model Based ◽  
Speed Accuracy

Abstract We forward a methodological approach, using model-based cluster analyses, and ambulatory assessments of cognition (2 indicators from each task), to derive subgroups of interest for tailored clinical follow-up in a longitudinal framework. Community dwelling adults were asked to complete 14 consecutive days of ecological momentary assessments (EMAs) using smartphones, including measures of cognitive performance, and self-reported physical and mental health outcomes (e.g., stress, memory complaints, depression, pain). A stable four-cluster solution emerged, labelled as: (1) a high-risk cognitive group (13%; most memory complaints, slowest performing, more memory errors); (2) subjective risk group (42%; highest levels of somatic and cognitive complaints); (3) normative aging (28%; intermediate cognitive performance -- speed/accuracy); (4) super-cognitive agers (17%; fastest speed, best memory). In conclusion, these findings highlight the potential of a cluster-based approach for risk classification, uncovering different profiles of poor performance that may represent different etiologies.

scholarly journals Emotions and learning in the chemistry laboratory

2016 ◽  
Vol 4 (2) ◽  
pp. 107-119
Author(s):  
Minna Tiainen ◽  
Heidi Pietilä ◽  
Sanna Tyni
Keyword(s):  
Learning Outcomes ◽  
Full Text ◽  
Learning Experiences ◽  
Chemistry Laboratory ◽  
Quality Teaching ◽  
First Year ◽  
Two Dimensional ◽  
Laboratory Studies ◽  
Laboratory Course ◽  
Model Based

In this study, the first-year chemistry laboratory course was renewed and made more intensive, three weeks course. Students’ experiences of the renewed course were examined by analyzing their learning diaries which they were encouraged to keep during the whole course. The purpose of this study was to find out how the intense coursework affects students’ emotions and learning experiences. Thus, the learning diaries were analyzed in order to find out different emotions that students experienced during the course. These emotions were then classified and represented using a model based on a two-dimensional emotion theory. Diversity of students’ emotions during the course gave us important information how emotions influenced on student’s learning and achievement. For teacher it is valuable to understand and deal with the emotions experienced by students while planning and carrying out the laboratory course. This enables not only higher quality teaching, but also more positive learning outcomes for students regarding their chemistry laboratory studies. FULL TEXT IN FINNISH.

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