Learning, Design, and Technology

Spector, Michael; Lockee, Barbara B.; Childress, Marcus

doi:10.1007/978-3-319-17727-4

Cited by 31 publications

(20 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Many authors have defined and developed learning analytics in the last 2013 years, by enabling data collected in learning management systems (LMS) to problem in child development during the learning process. The learning analytics and game-based learning can encourage the creation of more effective educational games and also help produce the maximum in the learning process (Freire et al, 2016). Utilizing well-developed K-12 learning internationally, through the use of platforms such as computers, laptops, tablets, and mobile devices for child development processes in learning models that are able to foster children's literacy skills learning media and collaborative learning models in basic education can be used in early childhood education.…”

Section: Discussionmentioning

confidence: 99%

Learning Analytics Contribution in Education and Child Development: A Review on Learning Analytics

Agus¹,

Samuri²

2018

AJATeL

View full text Add to dashboard Cite

Learning Analytics is a new field of research that appears as a link between educator data and students. The Learning Analytics is also able to provide information about decision making to understand and optimise the learning process. Early childhood education is believed to be very important because the learner is open and always tries new things and is considered very meaningful for future processes in the development of all aspects of their personality. In this study, we aimed at investigating the application of learning analytics and how the learning process on child development in early childhood education. The Article Search Process is carried out on two databases, ScienceDirect and IEEE. In this study, the most important keywords are Learning Analytics and early childhood. The results of the search are 45 articles: (31/45) ScienceDirect and (14/45) IEEE, from 2012 to 2017. They are thoroughly explored in the Learning Analytics process, data collection and pre-processing, analysis and action, and post-processing. The process of data collection is done by implementing Online Systems or Game-Based Learning: 58% e-Learning systems, 27% Learning Analytics systems, and 15% Game-based learning. Many research was conducted on samples from Post graduate, High school and Elementary school. The results showed that early childhood education had the advantage of the use of the new technology and in enchancing the child's knowledge and skills. Such as creativity and logical intelligence in the introduction of shapes and numbers. In the further study, the concept of Learning Analytics in the form of assessment and feedback that is given to support the improvement of the objectivity in the learning process by collaborating with educational games which can be another beneficial to the early childhood education. Objective assessment and feedback may be the monitor and prediction which will also be analised for the efficiency and effectiveness in the learning proces through the use of the technology.

show abstract

Section: Discussionmentioning

confidence: 99%

Learning Analytics Contribution in Education and Child Development: A Review on Learning Analytics

Agus¹,

Samuri²

2018

AJATeL

View full text Add to dashboard Cite

show abstract

“…But still, the analytics results did not provide information about how to utilize the results in the learning process. Unlike [31], which developed a model to standardize the variables of data collected in gamification and then converted them to sequential streams to be analyzed. Yet, the developed API was concerned only with the interaction data.…”

Section: A Analytics Without Adaptationmentioning

confidence: 99%

“…Even though some studies addressed adaptation, they ignored the gamification concept, and vice versa. Moreover, most of the research studies have not handled the educational game as a set of dependent OERs/LOs, making them difficult to be reused, shared, modified, or adapted [12]. Additionally, studies mainly perform learning analytics targeted to the teachers, or for the learning process itself, keeping the learners out of the equation.…”

Section: Introductionmentioning

confidence: 99%

Learners on Focus: Visualizing Analytics Through an Integrated Model for Learning Analytics in Adaptive Gamified E-Learning

2020

View full text Add to dashboard Cite

During the Coronavirus pandemic, e-learning systems have proven to be an essential pillar for education. This raises to surface what many studies have addressed earlier; creating a platform that completes the traditional classroom work and maximizes the effectiveness of learning outcomes. Striving to achieve such platform, studies have considered gamifying and personalizing the educational resources for the adaptation of educational systems as per the intended learners through intensive learning analytics. But was the learner really a part of the adaptation process taking place? Learning analytics are usually designed to the course's adaptation and solely for the teachers. Thus, learning analytics in gamified adaptive educational systems involving the course, teachers and learners together are still under investigation. In this study, the Personalized Adaptive Gamified E-learning (PAGE) model is introduced to extend MOOCs by providing new satisfactory levels of learning analytics and visualization in the rich e-learning process that supports the learner's intervention in the resultant learning analytics. The proposed Learning analytics have been developed to make the necessary adaptation to the course and learner's learning flow, as well as visualizing the process and adaptation decisions to the learners. Results show a positive potential towards learning adaptation and visualization, and a necessity to provide an additional focus for the gamification concept.

show abstract

“…This is to further evaluate the effectiveness of the SGH at presenting and exploring historical activity, achieving its learning objectives, and being an engaging game experience, and finally also to inform future SGH projects. Of these methods, in-game analytics has received particular interest in recent years for serious games (also known as gaming learning analytics or GLA) and can offer powerful insights by detecting a player's in-game actions, aggregating the data for many players over many play sessions, and analysing the data (Freire et al 2016). An interesting avenue for further research work will be to further integrate datadriven analytics into the evaluation of how well an SGH can bridge activity contexts.…”

Section: Labour Divisionmentioning

confidence: 99%

A model of heritage content to support the design and analysis of video games for history education

Hanes

Stone

2018

J. Comput. Educ.

View full text Add to dashboard Cite

In recent years, increasing academic attention has been focused on the educational potential of video games. Serious games for heritage applications have received much interest, and many examples are well documented in the literature. Many frameworks and methodologies have been proposed for how to design serious games, yet there is a lack of guidance for how to embed heritage information in the mechanics and content of these games. There are also many examples of commercial (non-serious) games that contain heritage content, and there is interest in how these games can be used in educational contexts. However, these games are designed primarily for entertainment purposes, without pedagogical foundations and with limited historical accuracy. There is currently a lack of a rigorous, scientific approach to support the critical analysis of the content of these games and to inform their use within learning settings. In this paper, we propose that the above issues are related by a lack of definitions of heritage content in the video game medium. We describe a model that defines how historical information can be presented in a video game at a content level and demonstrate how it can be applied to the analysis of the content in a commercial historical game. Finally, we propose a novel methodology based on activity theory to guide the design of serious games, based on pre-defined heritage instructional content. The findings are relevant both to educators who wish to use heritage video games, and to designers of serious games for heritage.

show abstract

Learning, Design, and Technology

Cited by 31 publications

References 0 publications

Learning Analytics Contribution in Education and Child Development: A Review on Learning Analytics

Learning Analytics Contribution in Education and Child Development: A Review on Learning Analytics

Learners on Focus: Visualizing Analytics Through an Integrated Model for Learning Analytics in Adaptive Gamified E-Learning

A model of heritage content to support the design and analysis of video games for history education

Contact Info

Product

Resources

About