Design Gaming for Learning Systems Intelligence in Socio‐Emotional Systems

2020 ◽  
Author(s):  
Raimo P. Hämäläinen ◽  
Kata‐Riikka Kumpulainen ◽  
J.Tuomas Harviainen ◽  
Esa Saarinen
Keyword(s):  
Learning Systems ◽  
Systems Intelligence ◽  
Emotional Systems

Assessment of Cognitive Load in Multimedia Learning Using Dual-Task Methodology

2002 ◽  
Vol 49 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Roland Brünken ◽  
Susan Steinbacher ◽  
Jan L. Plass ◽  
Detlev Leutner
Keyword(s):  
Cognitive Load ◽  
Dual Task ◽  
Cognitive Load Theory ◽  
Multimedia Learning ◽  
Learning Systems ◽  
Learning Materials ◽  
New Approach ◽  
Direct Assessment ◽  
Load Theory ◽  
Audiovisual Presentation

Abstract. In two pilot experiments, a new approach for the direct assessment of cognitive load during multimedia learning was tested that uses dual-task methodology. Using this approach, we obtained the same pattern of cognitive load as predicted by cognitive load theory when applied to multimedia learning: The audiovisual presentation of text-based and picture-based learning materials induced less cognitive load than the visual-only presentation of the same material. The findings confirm the utility of dual-task methodology as a promising approach for the assessment of cognitive load induced by complex multimedia learning systems.

Platform for Analysing and Encouraging Student Activity on Contest and E-learning Systems

2018 ◽  
Vol 12 ◽  
pp. 85-98
Author(s):  
Bojan Kostadinov ◽  
Mile Jovanov ◽  
Emil STANKOV
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Educational Policy ◽  
Learning Systems ◽  
Data Sources ◽  
Or Education ◽  
Student Activity ◽  
The World ◽  
E Learning ◽  
Analyse Data

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.

THE USE OF ICT IN ISLAMIC EDUCATION (PAI) LEARNING AT SCHOOL: A Case Study on Integrated Islamic High School (SMA-IT) Ummul Quro Bogor

2020 ◽  
Author(s):  
Farida Hanun
Keyword(s):  
High School ◽  
Learning Process ◽  
Research Method ◽  
Qualitative Approach ◽  
Learning Systems ◽  
Government Support ◽  
Islamic Education ◽  
Inhibiting Factors ◽  
The Impact

This study aims to obtain a description related to the learning of PAI by using ICT and how the impact of the use of ICT on PAI learning systems in the classroom. The research method uses a qualitative approach in the integrated Islamic high school Ummul Quro Bogor, West Java. The results showed that a) there were four stages of using ICT in the learning process, namely; emerging, applying, integrating dan transforming. PAI teachers are already at the integrating stage. In other words, ICT has been integrated into the PAI learning curriculum. b) supporting factors for the use of ICT are the existence of ICT support facilities, the availability of qualified educators, the commitment of the school to implement ICT in every PAI learning. c) Inhibiting factors in the use of ICT are aspects of financing ICT facilities require a large budget. Some elderly teachers have difficulty using ICT in the learning process. Besides, the internet network is unstable. d) The impact of the use of ICT is very significant on PAI learning process. e) the existence of ICT devices not only as a support but already as an important component in the education system. The research led to the recommendation of the need for government support in the form of concern for ICT in terms of policies, facilities, workforce, budget, and organizing training in the use of ICT for PAI teachers to improve their professionalism. Therefore, further research is suggested regarding the effectiveness of the use of ICT in the learning process of PAI.

Robot Teaching, Pedagogy, and Policy

2020 ◽  
pp. 787-803
Author(s):  
Elana Zeide
Keyword(s):  
Artificial Intelligence ◽  
Analytical Methods ◽  
Personalized Learning ◽  
Educational Process ◽  
Learning Systems ◽  
Policy Decisions ◽  
Public Discussion ◽  
Teaching Pedagogy ◽  
Do So

This chapter looks at the use of artificial intelligence (AI) in education, which immediately conjures the fantasy of robot teachers, as well as fears that robot teachers will replace their human counterparts. However, AI tools impact much more than instructional choices. Personalized learning systems take on a whole host of other educational roles as well, fundamentally reconfiguring education in the process. They not only perform the functions of robot teachers but also make pedagogical and policy decisions typically left to teachers and policymakers. Their design, affordances, analytical methods, and visualization dashboards construct a technological, computational, and statistical infrastructure that literally codifies what students learn, how they are assessed, and what standards they must meet. However, school procurement and implementation of these systems are rarely part of public discussion. If they are to remain relevant to the educational process itself, as opposed to just its packaging and context, schools and their stakeholders must be more proactive in demanding information from technology providers and setting internal protocols to ensure effective and consistent implementation. Those who choose to outsource instructional functions should do so with sufficient transparency mechanisms in place to ensure professional oversight guided by well-informed debate.

scholarly journals A meta-analysis on individual differences in primary emotional systems and Big Five personality traits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Davide Marengo ◽  
Kenneth L. Davis ◽  
Gökçe Özkarar Gradwohl ◽  
Christian Montag
Keyword(s):  
Individual Differences ◽  
Personality Traits ◽  
Big Five ◽  
Mammalian Species ◽  
Theoretical Perspective ◽  
Big Five Personality Traits ◽  
Self Report ◽  
Big Five Personality ◽  
Affective Neuroscience ◽  
Emotional Systems

AbstractThe Affective Neuroscience Personality Scales (ANPS) were constructed as a self-report assessment to measure individual differences in Jaak Panksepp’s cross-species primary emotional systems: SEEKING, PLAY, CARE (positive emotions) and FEAR, SADNESS, ANGER (negative emotions). Beginning with the first published work on the ANPS in 2003, individual differences on the ANPS measures of these six primary emotional systems have been consistently linked to Big Five personality traits. From a theoretical perspective, these primary emotional systems arising from subcortical regions, shed light on the nature of the Big Five personality traits from an evolutionary perspective, because each of these primary emotional systems represent a tool for survival endowing mammalian species with inherited behavioral programs to react appropriately to complex environments. The present work revisited 21 available samples where both ANPS and Big Five measures have been administered. Our meta-analytical analysis provides solid evidence that high SEEKING relates to high Openness to Experience, high PLAY to high Extraversion, high CARE/low ANGER to high Agreeableness and high FEAR/SADNESS/ANGER to high Neuroticism. This seems to be true regardless of the ANPS inventory chosen, although much more work is needed in this area. Associations between primary emotional systems and Conscientiousness were in the lower effect size area across all six primary emotions, thereby supporting the idea that Conscientiousness rather seems to be less directly related with the subcortical primary emotions and likely is the most cognitive/cortical personality construct out of the Big Five. In sum, the present work underlines the idea that individual differences in primary emotional systems represent evolutionarily ancient foundations of human personality, given their a) meaningful links to the prominent Big Five model and b) their origins lying in subcortical areas of the human brain.

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