Which types of learners are suitable for augmented reality? A fuzzy set analysis of learning outcomes configurations from the perspective of individual differences

Author(s):  
Yizhou Ling ◽  
Pengfei Zhu ◽  
Jiayan Yu
Author(s):  
Ana Villanueva ◽  
Ziyi Liu ◽  
Yoshimasa Kitaguchi ◽  
Zhengzhe Zhu ◽  
Kylie Peppler ◽  
...  

AbstractAugmented reality (AR) is a unique, hands-on tool to deliver information. However, its educational value has been mainly demonstrated empirically so far. In this paper, we present a modeling approach to provide users with mastery of a skill, using AR learning content to implement an educational curriculum. We illustrate the potential of this approach by applying this to an important but pervasively misunderstood area of STEM learning, electrical circuitry. Unlike previous cognitive assessment models, we break down the area into microskills—the smallest segmentation of this knowledge—and concrete learning outcomes for each. This model empowers the user to perform a variety of tasks that are conducive to the acquisition of the skill. We also provide a classification of microskills and how to design them in an AR environment. Our results demonstrated that aligning the AR technology to specific learning objectives paves the way for high quality assessment, teaching, and learning.


2018 ◽  
Vol 58 (2) ◽  
pp. 203-217 ◽  
Author(s):  
Anna Katharina Bader ◽  
Lena Elisabeth Kemper ◽  
Fabian Jintae Froese

2021 ◽  
pp. 104383
Author(s):  
Abdullah M. Baabdullah ◽  
Abdulellah A. Alsulaimani ◽  
Alhasan Allamnakhrah ◽  
Ali Abdallah Alalwan ◽  
Yogesh K. Dwivedi ◽  
...  

Author(s):  
Hokyin Lai ◽  
Minhong Wang ◽  
Huaiqing Wang

Adaptive learning approaches support learners to achieve the intended learning outcomes through a personalized way. Previous studies mistakenly treat adaptive e-Learning as personalizing the presentation style of the learning materials, which is not completely correct. The main idea of adaptive learning is to personalize the earning content in a way that can cope with individual differences in aptitude. In this study, an adaptive learning model is designed based on the Aptitude-Treatment Interaction theory and Constructive Alignment Model. The model aims at improving students’ learning outcomes through enhancing their intrinsic motivation to learn. This model is operationalized with a multi-agent framework and is validated under a controlled laboratory setting. The result is quite promising. The individual differences of students, especially in the experimental group, have been narrowed significantly. Students who have difficulties in learning show significant improvement after the test. However, the longitudinal effect of this model is not tested in this study and will be studied in the future.


Author(s):  
Filiz Kalelioglu ◽  
Yasemin Gulbahar

In this chapter, numerous educational activities are presented for instructors in order to address each type of multiple intelligences. Most probably, these educational activities are those which are already being experienced by many instructors. The key point here is that although students are exposed to many educational activities, instructors generally don’t have any idea or rather don’t consider the learning outcomes in terms of multiple intelligences. In general, assessment activities are based only on the chunk of knowledge that the student gains after any particular activity. In fact, instructors should deal with the effects and improvements in students other than just the knowledge, after engagement in educational activities. Thus, instructors should base their instructional plans on a theoretical basis, especially when integrating technology into their courses. Hence, the development and changing activities and other tasks of social software according to the multiple intelligences that underline individual differences were discussed briefly in this chapter.


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