Generating Adaptive Learning Games to Multiple Mobile Platforms

Mastering Programming Skills with the Use of Adaptive Learning Games

Communications in Computer and Information Science - Knowledge-Based Software Engineering ◽

10.1007/978-3-319-11854-3_14 ◽

2014 ◽

pp. 144-155 ◽

Cited By ~ 2

Author(s):

Ofut Ogar ◽

Olga Shabalina ◽

Alexander Davtyan ◽

Alexey Kizim

Keyword(s):

Adaptive Learning ◽

Learning Games ◽

Programming Skills

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Investigation of Emerging Trends in the E-Learning Field Using Latent Dirichlet Allocation

The International Review of Research in Open and Distributed Learning ◽

10.19173/irrodl.v22i2.5358 ◽

2021 ◽

Vol 22 (2) ◽

pp. 1-18

Author(s):

Fatih Gurcan ◽

Ozcan Ozyurt ◽

Nergiz Ercil Cagitay

Keyword(s):

Adaptive Learning ◽

Teaching And Learning ◽

Latent Dirichlet Allocation ◽

High Volume ◽

Learning Systems ◽

Mobile Platforms ◽

Emerging Trends ◽

E Learning ◽

Learning Factors ◽

Dirichlet Allocation

E-learning studies are becoming very important today as they provide alternatives and support to all types of teaching and learning programs. The effect of the COVID-19 pandemic on educational systems has further increased the significance of e-learning. Accordingly, gaining a full understanding of the general topics and trends in e-learning studies is critical for a deeper comprehension of the field. There are many studies that provide such a picture of the e-learning field, but the limitation is that they do not examine the field as a whole. This study aimed to investigate the emerging trends in the e-learning field by implementing a topic modeling analysis based on latent Dirichlet allocation (LDA) on 41,925 peer-reviewed journal articles published between 2000 and 2019. The analysis revealed 16 topics reflecting emerging trends and developments in the e-learning field. Among these, the topics “MOOC,” “learning assessment,” and “e-learning systems” were found to be key topics in the field, with a consistently high volume. In addition, the topics of “learning algorithms,” “learning factors,” and “adaptive learning” were observed to have the highest overall acceleration, with the first two identified as having a higher acceleration in recent years. Going by these results, it is concluded that the next decade of e-learning studies will focus on learning factors and algorithms, which will possibly create a baseline for more individualized and adaptive mobile platforms. In other words, after a certain maturity level is reached by better understanding the learning process through these identified learning factors and algorithms, the next generation of e-learning systems will be built on individualized and adaptive learning environments. These insights could be useful for e-learning communities to improve their research efforts and their applications in the field accordingly.

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Science Learning Games for Mobile Platforms

Encyclopedia of Mobile Phone Behavior ◽

10.4018/978-1-4666-8239-9.ch047 ◽

2015 ◽

pp. 562-574 ◽

Cited By ~ 2

Author(s):

Gabriela Trindade Perry ◽

Marcelo Leandro Eichler

Keyword(s):

Mobile Technology ◽

Science Learning ◽

Internet Access ◽

Research Area ◽

Learning Theories ◽

Mobile Platforms ◽

Continuous Increase ◽

Learning Games ◽

Processing Power ◽

Simulation Based

Science learning, though bound to broader learning theories, is a research area on its own. Science subject domains share special characteristics: they are like wide nested concept nets - most of which are either abstract or not available to direct observation. For this reason the authors advocate that game-based and simulation-based pedagogies are promising tools for learning. Recently the authors have noticed two characteristics that would further empower the use of these strategies: (1) the widespread use of mobile technology among youngsters with continuous increase in processing power and internet access, and (2) the strong affordances games could provide in learning activities.

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Using Popular Mobile Devices in Voice Therapy

Perspectives on Voice and Voice Disorders ◽

10.1044/vvd23.3.82 ◽

2013 ◽

Vol 23 (3) ◽

pp. 82-87 ◽

Cited By ~ 1

Author(s):

Eva van Leer

Keyword(s):

Exercise Behavior ◽

Voice Therapy ◽

Pure Oxygen ◽

Mobile Platforms ◽

Self Monitoring ◽

Web Based ◽

Motivational Messages ◽

Related Information ◽

Health Related ◽

Tailored Approach

Mobile tools are increasingly available to help individuals monitor their progress toward health behavior goals. Commonly known commercial products for health and fitness self-monitoring include wearable devices such as the Fitbit© and Nike + Pedometer© that work independently or in conjunction with mobile platforms (e.g., smartphones, media players) as well as web-based interfaces. These tools track and graph exercise behavior, provide motivational messages, offer health-related information, and allow users to share their accomplishments via social media. Approximately 2 million software programs or “apps” have been designed for mobile platforms (Pure Oxygen Mobile, 2013), many of which are health-related. The development of mobile health devices and applications is advancing so quickly that the Food and Drug Administration issued a Guidance statement with the purpose of defining mobile medical applications and describing a tailored approach to their regulation.

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