Games for Learning and Learning Transfer

2010 ◽  
pp. 113-126 ◽  
Author(s):  
Gearóid Ó Súilleabháin ◽  
Julie-Ann Sime
Keyword(s):  
Deep Learning ◽  
Video Games ◽  
Learning Transfer ◽  
Learning Processes ◽  
Research Practice ◽  
Research Subjects ◽  
Game Play ◽  
Games For Learning ◽  
Extended Practice ◽  
Research Findings

Research findings are at best mixed with regard to the effectiveness of computer and video games in promoting learning transfer or learning, but much of this research makes use of the same unsuccessful methods of classic transfer experiments which offered research subjects limited initial practice in the learning to be transferred. Learning transfer however, like expertise, may need to be based on extended practice, an idea supported by studies of habitual or expert game players and recent non-game related developments in transfer research. Practice however must be joined to a certain kind of game complexity and cognitive or experiential game fidelity before deep learning and instances of significant transfer can be facilitated. Implications of these transfer conditions for the design of games for transfer are discussed as well as the need for research with regard to the various learning processes underlying the game-play behaviour of expert and habitual gamers.

scholarly journals Privacy of Clinical Research Subjects: An Integrative Literature Review

2018 ◽  
Vol 14 (1) ◽  
pp. 33-48 ◽  
Author(s):  
Sanna-Maria Nurmi ◽  
Mari Kangasniemi ◽  
Arja Halkoaho ◽  
Anna-Maija Pietilä
Keyword(s):  
Clinical Research ◽  
Privacy Protection ◽  
Personal Data ◽  
Comparison Method ◽  
Health Data ◽  
The Body ◽  
Social Benefits ◽  
Theoretical Studies ◽  
Research Practice ◽  
Research Subjects

With changes in clinical research practice, the importance of a study-subject’s privacy and the confidentiality of their personal data is growing. However, the body of research is fragmented, and a synthesis of work in this area is lacking. Accordingly, an integrative review was performed, guided by Whittemore and Knafl’s work. Data from PubMed, Scopus, and CINAHL searches from January 2012 to February 2017 were analyzed via the constant comparison method. From 16 empirical and theoretical studies, six topical aspects were identified: the evolving nature of health data in clinical research, sharing of health data, the challenges of anonymizing data, collaboration among stakeholders, the complexity of regulation, and ethics-related tension between social benefits and privacy. Study subjects’ privacy is an increasingly important ethics principle for clinical research, and privacy protection is rendered even more challenging by changing research practice.

The older player of digital games: A classification based on perceived need satisfaction

2014 ◽  
Vol 39 (1) ◽  
Author(s):  
Bob De Schutter ◽  
Steven Malliet
Keyword(s):  
Older Adults ◽  
Video Games ◽  
Qualitative Study ◽  
Digital Games ◽  
Need Satisfaction ◽  
Digital Game ◽  
Game Play ◽  
Perceived Need ◽  
Freedom Fighters ◽  
Larger Sample

AbstractThe current study aims to integrate the findings of previous research on the use of video games by older adults by applying the Uses & Gratifications (U&GT) paradigm (Blumler and Katz, 1974). A qualitative study was performed with 35 participants aged between 50 and 74, who were selected from a larger sample of 213. Based upon their primary playing motives and the gratifications they obtain from digital game play, a classification was developed, resulting in five categories of older adults who actively play games: “time wasters”, “freedom fighters”, “compensators”, “value seekers” and “ludophiles”.

scholarly journals Considerations for comparing video-game AI agents with humans

2020 ◽  
Author(s):  
Christopher R Madan
Keyword(s):  
Video Games ◽  
Video Game ◽  
Reaction Times ◽  
Game Play ◽  
Complex Action ◽  
Potential Approach ◽  
Video Game Play ◽  
Game Ai ◽  
Strategy Games ◽  
Action Sequences

Video games are sometimes used as environments to evaluate AI agents' ability to develop and execute complex action sequences to maximize a defined reward. However, humans cannot match the fine precision of timed actions of AI agents--in games such as StarCraft, build orders take the place of chess opening gambits. However, unlike strategy games, such as chess and go, video games also rely heavily on sensorimotor precision. If the `finding' was merely that AI agents have superhuman reaction times and precision, none would be surprised. The goal is rather to look at adaptive reasoning and strategies produced by AI agents that may replicate human approaches or even result in strategies not previously produced by humans.Here I will provide: (1) an overview of observations where AI agents are perhaps not being fairly evaluated relative to humans, (2) a potential approach for making this comparison more appropriate, and (3) highlight some important recent advances in video-game play provided by AI agents.

scholarly journals An Improved Deep Learning Algorithm for Risk Prediction of Corporate Internet Reporting

2020 ◽  
Vol 34 (4) ◽  
pp. 437-444
Author(s):  
Lingyan Ou ◽  
Ling Chen
Keyword(s):  
Deep Learning ◽  
Risk Prediction ◽  
Short Term Memory ◽  
Learning Algorithm ◽  
Moving Average ◽  
Arma Model ◽  
Evaluation Index System ◽  
Online Information ◽  
Deep Learning Algorithm ◽  
Research Findings

Corporate internet reporting (CIR) has such advantages as the strong timeliness, large amount, and wide coverage of financial information. However, the CIR, like any other online information, faces various risks. With the aid of the increasingly sophisticated artificial intelligence (AI) technology, this paper proposes an improved deep learning algorithm for the prediction of CIR risks, aiming to improve the accuracy of CIR risk prediction. After building a reasonable evaluation index system (EIS) for CIR risks, the data involved in risk rating and the prediction of risk transmission effect (RTE) were subject to structured feature extraction and time series construction. Next, a combinatory CIR risk prediction model was established by combining the autoregressive moving average (ARMA) model with long short-term memory (LSTM). The former is good at depicting linear series, and the latter excels in describing nonlinear series. Experimental results demonstrate the effectiveness of the ARMA-LSTM model. The research findings provide a good reference for applying AI technology in risk prediction of other areas.

Being a Post-Learner With Virtual Worlds

2019 ◽  
pp. 185-204 ◽  
Author(s):  
Ferhan Şahin ◽  
Ezgi Doğan
Keyword(s):  
21St Century ◽  
Virtual Worlds ◽  
Learning Transfer ◽  
Human Life ◽  
Learning Processes ◽  
Artificial Organs ◽  
Learning Context ◽  
3 Dimensional

Transhumanism, which emerges as a movement of thought, stands out with the developments such as artificial organs, brain-to-brain knowledge and learning transfer and smart robots in the 21st century. One of these technologies, where we see early applications with the goal of reaching the post-human, is the virtual worlds. Some features of the post-humans, which can now be experienced through 3 dimensional immersive virtual worlds in a certain scale, also reveal the fact that the existing virtual worlds are a limited simulation of a transhumanist future. While the virtual worlds and transhumanism perspective is expected to be effective in various areas of human life, it will be inevitable for these effects to manifest themselves in learning processes. In this sense, evaluation of surrounding learning by virtual worlds is the main objective of this chapter. For this purpose, virtual worlds in transhumanism age were tried to be evaluated under learning context by using anime series and film samples which are yet considered as sci-fi.

Digital Storytelling as a Self-Regulated Learning Tool

2019 ◽  
pp. 209-232 ◽  
Author(s):  
Sinan Kaya
Keyword(s):  
Learning Process ◽  
Digital Storytelling ◽  
Learning Processes ◽  
Learning Tools ◽  
Learning Tool ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Digital Stories ◽  
Research Findings ◽  
Made In

The purpose of this chapter is, as a self-regulated learning tool, to focus on digital storytelling by uncovering relationship between digital storytelling and self-regulated learning process/based on research findings made in the its field. Within this focus, firstly, concept of digital storytelling was theoretically addressed; researches made in learning-teaching for use have been presented; later, self-regulated learning processes and strategies have been defined and given examples. Finally, research findings on the use of digital stories as self-regulated learning tools have been shared.

Learning Processes and Violent Video Games

2011 ◽  
pp. 1807-1822
Author(s):  
Edward L. Swing ◽  
Douglas A. Gentile ◽  
Craig A. Anderson
Keyword(s):  
Video Games ◽  
Learning Outcomes ◽  
Learning Processes ◽  
Long Term Effects ◽  
Violent Video Games ◽  
Improved Performance ◽  
Learning Principles ◽  
General Learning Model ◽  
Basic Learning

Though video games can produce desirable learning outcomes, such as improved performance in school subjects, they also can produce undesirable outcomes, such as increased aggression. Some of the basic learning principles that make video games (particularly violent video games) effective at teaching are discussed in this chapter. A general learning model is presented to explain how video games can produce a variety of effects in their users. This model explains both the immediate, short term effects and cumulative, long term effects of video games. Implications of these principles are discussed in relation to education. The issue of addressing violent video games’ effects on aggression is also examined.

The Exploration of Autonomous Vehicles

2022 ◽  
pp. 930-944
Author(s):  
Anthony J. Gephardt ◽  
Elizabeth Baoying Wang
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Intelligent Agents ◽  
Autonomous Vehicles ◽  
Learning Processes ◽  
Artificial Intelligent ◽  
The World ◽  
History Of ◽  
The Creation

This chapter explores the world of autonomous vehicles. Starting from the beginning, it covers the history of the automobile dating back to 1769. It explains how the first production automobile came about in 1885. The chapter dives into the history of auto safety, ranging from seatbelts to full-on autonomous features. One of the main focuses is the creation and implementation of artificial intelligent (AI), neural networks, intelligent agents, and deep Learning Processes. Combining the hardware on the vehicle with the intelligence of AI creates what we know as autonomous vehicles today.

Game-Based Learning

2012 ◽  
pp. 628-647 ◽  
Author(s):  
Sylke Vandercruysse ◽  
Mieke Vandewaetere ◽  
Geraldine Clarebout
Keyword(s):  
Instructional Technology ◽  
Video Games ◽  
Literature Search ◽  
Educational Games ◽  
Systematic Literature Search ◽  
Positive Outcomes ◽  
Game Based Learning ◽  
Games For Learning ◽  
Context Variables ◽  
Positive Effect

A new interest in the use of video games for learning has emerged, and a number of claims are made with respect to the effectiveness of games in education. These educational games are considered as new instructional technology with great potential. The suggested positive outcomes and effects have been mentioned repeatedly. In this review, the learning effects of educational games are studied in order to gain more insights into the conditions under which a game may be effective for learning. A systematic literature search in three databases was conducted. Some studies reported a positive effect on learning and motivation, but this is moderated by different learner variables and depends on different context variables. Next to this, the effectivity research on game-based learning is highly susceptible to a muddle of approaches, methodologies, and descriptions of gaming for educational purposes.

Exploring Complex Intertextual Interactions in Video Games

2016 ◽  
pp. 108-128
Author(s):  
Kathy Sanford ◽  
Timothy Frank Hopper ◽  
Jamie Burren
Keyword(s):  
Video Games ◽  
Language Arts ◽  
Video Game ◽  
Formal Education ◽  
Teaching Tool ◽  
Game Play ◽  
Video Game Play ◽  
Class A ◽  
Video Gamers ◽  
Grade 11

This chapter explores the intertextual nature of video games. Video games are inherently intertextual and have utilized intertextuality in profound ways to engage players and make meaning. Youth who play video games demonstrate complex intertextual literacies that enable them to construct and share understandings across game genres. However, video game literacy is noticeably absent from formal education. This chapter draws from bi-monthly meetings with a group of youth video gamers. Video game sessions focused on exploring aspect of video game play such as learning and civic engagements. Each session was video recorded and coded using You Tube annotation tools. Focusing on intertextuality as an organizing construct, the chapter reports on five themes that emerged that were then used to help explore the use of video games as teaching tool in a grade 11 Language Arts class. A critical concept that emerged was the idea of complex intertextual literacy that frames and enables adolescents' engagement with video games.

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