scholarly journals The Effects of Task Selection Approaches to Emphasis Manipulation on Cognitive Load and Knowledge Transfer

2021 ◽  
Vol 9 (4) ◽  
pp. 83-101
Author(s):  
Seohyun Choi ◽  
Jaewon Jung ◽  
Dongsik Kim
Keyword(s):  
Knowledge Transfer ◽  
Cognitive Load ◽  
Skill Acquisition ◽  
Transfer Test ◽  
Learning Task ◽  
Selection Strategy ◽  
Learning Context ◽  
Task Selection ◽  
Learning Tasks ◽  
The Impact

Emphasis manipulation is a way to help learners by directing their attention to particular subcomponents of a learning task. This study investigated the effects of different approaches to emphasis manipulation on knowledge transfer and cognitive load. This was done by examining the impact of three task selection strategies: system-controlled, learner-controlled, and shared-controlled. Forty-five students (n = 45) in the first or second year of high school were randomly assigned to three groups and each group used a different type of task selection to manipulate emphasis in a complex learning context. The system-controlled group carried out learning tasks that were identified as essential by the system. The learner-controlled group selected and carried out learning tasks they needed to learn. The shared-controlled group chose and carried out learning tasks that they wanted to learn from a list of suggested learning tasks. The tasks had four learning phases: pre-test, training, mental-effort rating, and transfer test. After participants completed the training, their cognitive load was measured. One week after the training, a transfer test was conducted to measure the constituent skill acquisition. The findings revealed that the system-controlled task selection strategy was the most effective in optimizing cognitive load and enhancing knowledge transfer. In addition, learners benefited from personalized guidance on learning task selection based on their expertise. Given that the shared-controlled task selection method was more effective thank the learner-controlled task selection, this study’s results indicate that learners should be provided with information about how to select learning tasks when they are allowed to do so.

The Impact of National Cultural Values on Intrinsic Motivation to Transfer Tacit Knowledge

2016 ◽  
Vol 12 (4) ◽  
pp. 1-19 ◽  
Author(s):  
Nicole Amanda Celestine ◽  
Chris Perryer
Keyword(s):  
Knowledge Transfer ◽  
Intrinsic Motivation ◽  
Tacit Knowledge ◽  
Cultural Values ◽  
Skill Acquisition ◽  
Future Research ◽  
Motivation To Transfer ◽  
The Uk ◽  
The Impact

This study examines the moderating effects of individuals' national cultural values on intrinsic motivation to engage in tacit knowledge transfer, through the lens of knowledge coaching. Using partial least squares analysis, survey data from 26 district managers (knowledge coaches) and 102 territory managers (protégés) from a large MNC's subsidiaries in Denmark, Ireland, Japan, Norway, Sweden and the UK is examined. In the first model, appertaining to the knowledge coaches, long-term orientation positively moderated the path between intrinsic motivation and perceived selling skill acquisition. For the corresponding pathway in the protégé model, collectivism and power distance attenuated the pathway. The implications for managers in terms of fostering intrinsic motivation to engage in knowledge transfer across a diversity of employees, and avenues for future research are discussed.

scholarly journals Sequential motor learning transfers from real to virtual environment

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Yuhi Takeo ◽  
Masayuki Hara ◽  
Yuna Shirakawa ◽  
Takashi Ikeda ◽  
Hisato Sugata
Keyword(s):  
Motor Learning ◽  
Virtual Environments ◽  
Virtual Environment ◽  
Motor Skills ◽  
Skill Acquisition ◽  
Learning Task ◽  
Button Press ◽  
Reaching Task ◽  
Learning Tasks ◽  
Task Order

Abstract Background Skill acquisition of motor learning between virtual environments (VEs) and real environments (REs) may be related. Although studies have previously examined the transfer of motor learning in VEs and REs through the same tasks, only a small number of studies have focused on studying the transfer of motor learning in VEs and REs by using different tasks. Thus, detailed effects of the transfer of motor skills between VEs and REs remain controversial. Here, we investigated the transfer of sequential motor learning between VEs and REs conditions. Methods Twenty-seven healthy volunteers performed two types of sequential motor learning tasks; a visually cued button-press task in RE (RE task) and a virtual reaching task in VE (VE task). Participants were randomly assigned to two groups in the task order; the first group was RE task followed by VE task and the second group was VE task followed by RE task. Subsequently, the response time in RE task and VE task was compared between the two groups respectively. Results The results showed that the sequential reaching task in VEs was facilitated after the sequential finger task in REs. Conclusions These findings suggested that the sequential reaching task in VEs can be facilitated by a motor learning task comprising the same sequential finger task in REs, even when a different task is applied.

scholarly journals Sequential Motor Learning Transfers from Real to Virtual Environment

2020 ◽  
Author(s):  
Yuhi Takeo ◽  
Masayuki Hara ◽  
Yuna Shirakawa ◽  
Takashi Ikeda ◽  
Hisato Sugata
Keyword(s):  
Motor Learning ◽  
Virtual Environments ◽  
Virtual Environment ◽  
Motor Skills ◽  
Skill Acquisition ◽  
Learning Task ◽  
Button Press ◽  
Reaching Task ◽  
Learning Tasks ◽  
Task Order

Abstract Background:Skill acquisition of motor learning between virtual environments (VEs) and real environments (REs) may be related. Although studies have previously examined the transfer of motor learning in VEs and REs through the same tasks, only a small number of studies have focused on studying the transfer of motor learning in VEs and REs by using different tasks. Thus, detailed effects of the transfer of motor skills between VEs and REs remain controversial. Here, we investigated the transfer of sequential motor learning between VEs and REs conditions.Methods:Twenty-seven healthy volunteers performed two types of sequential motor learning tasks; a visually cued button press task in RE (RE task) and a virtual reaching task in VE (VE task). Participants were randomly assigned to two groups in the task order; the first group was RE task followed by VE task and the second group was VE task followed by RE task. Subsequently, the response time in RE task and VE task was compared between the two groups respectively.Results:The results revealed that sequential motor learning was transferred when motor learning in VEs was performed after motor learning in REs, but not when motor learning in REs was performed after motor learning in VEs.Conclusions:These findings suggested that sequential motor learning in VEs can be facilitated by motor learning task consisting of the same sequence in REs even when different task is applied. These results may derive from the fact that motor learning in REs is more implicit than that in VEs.

Factors in Predicting Success in the Acquisition of Cognitive Skill

1988 ◽  
Vol 32 (14) ◽  
pp. 843-847
Author(s):  
Patrick C. Kyllonen
Keyword(s):  
Skill Acquisition ◽  
Conceptual Knowledge ◽  
Working Memory Capacity ◽  
Logic Gates ◽  
Learning Task ◽  
Factual Knowledge ◽  
Learning Tasks ◽  
Predicting Success ◽  
Learner Differences ◽  
And Performance

This paper reviews two studies that have examined the relationship between performance on basic cognitive tasks, administered on microcomputers, and performance on two learning tasks. One learning task involved computer programming, the other involved learning to trace signals through logic gates, a component of electronics troubleshooting skill. From previous research, we have established a four-source framework: we assume that observed learner differences are due to differences in processing speed; processing capacity; and the breadth, extent, and accessibility of conceptual knowledge and procedural and strategic skills. In both studies, we attempted to predict the proficiency (i.e., speed and accuracy) with which individuals were able to acquire skill in the domain area (programming, troubleshooting) as a function of their scores on the four cognitive factors. Each cognitive factor was indicated by performance on two computerized tests. Skill acquisition proficiency on the learning tasks was decomposed into separate scores for (a) speed of acquisition of the initial declarative foundations of the skill (the facts), (b) speed of acquisition of the ability to apply the factual knowledge to solve domain problems (the skill itself). In both studies, working memory capacity was the best predictor of both the speed with which domain facts were learned, and of one's ability to translate those facts into rules that could be employed in problem solving.

scholarly journals A network model of behavioural performance in a rule learning task

2018 ◽  
Vol 373 (1744) ◽  
pp. 20170275 ◽  
Author(s):  
Michael E. Hasselmo ◽  
Chantal E. Stern
Keyword(s):  
Individual Differences ◽  
Cognitive Function ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Rule Learning ◽  
Learning Task ◽  
Potential Contribution ◽  
Learning Context ◽  
Network Parameters ◽  
Learning Tasks

Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function. This article is part of the theme issue ‘Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences’.

Decision Aids for Generating Analytical Review Alternatives: The Impact of Goal Framing and Audit-Risk Level

2002 ◽  
Vol 14 (1) ◽  
pp. 157-177 ◽  
Author(s):  
Jennifer M. Mueller ◽  
John C. Anderson
Keyword(s):  
High Risk ◽  
Cognitive Load ◽  
Information Search ◽  
Decision Aid ◽  
Decision Aids ◽  
Risk Level ◽  
Audit Risk ◽  
Goal Framing ◽  
Analytical Review ◽  
The Impact

An auditor generating potential explanations for an unusual variance in analytical review may utilize a decision aid, which provides many explanations. However, circumstances of budgetary constraints and limited cognitive load deter an auditor from using a lengthy list of explanations in an information search. A two-way between-subjects design was created to investigate the effects of two complementary approaches to trimming down the lengthy list on the number of remaining explanations carried forward into an information search. These two approaches, which represent the same goal (reducing the list) but framed differently, are found to result in a significantly different number of remaining explanations, in both low- and high-risk audit environments. The results of the study suggest that the extent to which an auditor narrows the lengthy list of explanations is important to the implementation of decision aids in analytical review.

Preservice Music Teacher Identity Construction Through Metaphor

2020 ◽  
pp. 105708372098227
Author(s):  
Cynthia L. Wagoner
Keyword(s):  
Preservice Teachers ◽  
Identity Construction ◽  
Teacher Identity ◽  
Instrumental Music ◽  
Methods Course ◽  
Learning Context ◽  
Context Learning ◽  
Instrumental Methods ◽  
The Impact ◽  
Authentic Context

I investigated how preservice instrumental music teachers understand and describe their teacher identity through the use of metaphor in a one-semester instrumental methods course emphasizing authentic context learning. Twenty-five third-year instrumental methods course music education students created a personal metaphor to explore their professional identity construction. Preservice teacher metaphors were revisited throughout the semester, while students participated in an authentic context learning experience in an urban instrumental music classroom. Data sources included student artifacts, informal interviews, and observation/field notes. The impact of teaching within an authentic learning context appears to enrich the ways in which preservice teachers are able to articulate details of their metaphor descriptions. Through their reflections across the semester, preservice teachers demonstrated how personal metaphors were used to restructure their understandings of teacher identity and capture some of the complexities of becoming teachers.

scholarly journals Individualized embryo selection strategy developed by stacking machine learning model for better in vitro fertilization outcomes: an application study

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Qingsong Xi ◽  
Qiyu Yang ◽  
Meng Wang ◽  
Bo Huang ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
In Vitro Fertilization ◽  
Endometrial Thickness ◽  
Learning System ◽  
Embryo Selection ◽  
Selection Strategy ◽  
Application Study ◽  
Vitro Fertilization ◽  
The Impact

Abstract Background To minimize the rate of in vitro fertilization (IVF)- associated multiple-embryo gestation, significant efforts have been made. Previous studies related to machine learning in IVF mainly focused on selecting the top-quality embryos to improve outcomes, however, in patients with sub-optimal prognosis or with medium- or inferior-quality embryos, the selection between SET and DET could be perplexing. Methods This was an application study including 9211 patients with 10,076 embryos treated during 2016 to 2018, in Tongji Hospital, Wuhan, China. A hierarchical model was established using the machine learning system XGBoost, to learn embryo implantation potential and the impact of double embryos transfer (DET) simultaneously. The performance of the model was evaluated with the AUC of the ROC curve. Multiple regression analyses were also conducted on the 19 selected features to demonstrate the differences between feature importance for prediction and statistical relationship with outcomes. Results For a single embryo transfer (SET) pregnancy, the following variables remained significant: age, attempts at IVF, estradiol level on hCG day, and endometrial thickness. For DET pregnancy, age, attempts at IVF, endometrial thickness, and the newly added P1 + P2 remained significant. For DET twin risk, age, attempts at IVF, 2PN/ MII, and P1 × P2 remained significant. The algorithm was repeated 30 times, and averaged AUC of 0.7945, 0.8385, and 0.7229 were achieved for SET pregnancy, DET pregnancy, and DET twin risk, respectively. The trend of predictive and observed rates both in pregnancy and twin risk was basically identical. XGBoost outperformed the other two algorithms: logistic regression and classification and regression tree. Conclusion Artificial intelligence based on determinant-weighting analysis could offer an individualized embryo selection strategy for any given patient, and predict clinical pregnancy rate and twin risk, therefore optimizing clinical outcomes.

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