When adaptive learning is effective learning: comparison of an adaptive learning system to teacher-led instruction

Wang, Shuai; Christensen, Claire; Cui, Wei; Tong, Richard M.; Yarnall, Louise; Shear, Linda; Feng, Mingyu

doi:10.1080/10494820.2020.1808794

Cited by 97 publications

(39 citation statements)

References 20 publications

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“…Adaptive instruction can be defined as adjusting instructional plans provided by instructors in their instructional process according to students' learning differences. In other words, adaptive instruction can provide a personalized learning process according to students' needs (Wang et al, 2020). When using adaptive instruction, instructors have to design and revise their instructional plans according to students' differences and learning progress and modify their instructional modes to cope with the diverse needs of individual students.…”

Section: Adaptive Instructionmentioning

confidence: 99%

Learning Performance in Adaptive Learning Systems: A Case Study of Web Programming Learning Recommendations

Ling

Chiang

2022

Front. Psychol.

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Students often face challenges while learning computer programming because programming languages’ logic and visual presentations differ from human thought processes. If the course content does not closely match learners’ skill level, the learner cannot follow the learning process, resulting in frustration, low learning motivation, or abandonment. This research proposes a web programming learning recommendation system to provide students with personalized guidance and step-by-step learning planning. The system contains front-end and back-end web development instructions. It can create personalized learning paths to help learners achieve a sense of accomplishment. The system can help learners build self-confidence and improve learning effectiveness. In study 1, the recommendation system was developed based on the personal data and feedback of 41 professional web design engineers. The system uses C4.5 decision tree methods to develop a programming learning recommendation model to provide appropriate learning recommendations and establish personalized learning paths. The test group included 13 beginner programmers. After 4 weeks’ programming instructions in front-end and back-end web development, the learners were interviewed to understand their preferences and learning effectiveness. The results show that the effectiveness of the recommendation system is acceptable. In study 2, online real-time feedback and adaptive instruction platform is developed, which is different from the past adaptive curriculums mainly using the Internet platform and only the submitted assignments to determine the newly recommended learning process for students. The study found that the students’ learning performance in the adaptive instruction group is better than those in the fixed instruction group.

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Section: Adaptive Instructionmentioning

confidence: 99%

Learning Performance in Adaptive Learning Systems: A Case Study of Web Programming Learning Recommendations

Ling

Chiang

2022

Front. Psychol.

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“…For example, two studies examined how mobile learning systems were designed to help activate learners' relevant prior knowledge (Song et al, 2012) or automatically link to pre-requisite information (CP3.1; Hwang, Tsai, et al, 2012). Aligned to CP3.2, some adaptive learning systems were able to provide functions such as underlining, drawing on figures (Arroyo et al, 2014), and highlighting text with varying colours (Siddique et al, 2018) Abawi, 2015;Admiraal et al, 2020;Alcoholado et al, 2011;Basham et al, 2016;Kim et al, 2019;Looi et al, 2009;Martín-SanJosé et al, 2014;McCarthy, Liu, & Schauer, 2020;Phan, 2020;Phillips et al, 2020;Schmid & Petko, 2019;Song et al, 2012;Tsybulsky, 2020); Provide autonomy in improvisation to create meaningful contexts (Looi et al, 2009); Allow student to choose which mathematical task topics based on interest (Clinton & Walkington, 2019;Høgheim & Reber, 2015); Incorporate learner-selected vocabulary into learning content (Choi & Ma, 2015); Allow for customization of online learning texts with choice background colour, picture, font style (Ertem, 2013) Siddique et al, 2018;Standen et al, 2020;Su et al, 2006;Troussas et al, 2020;Tseng et al, 2008;Wang et al, 2020); Learning systems automatically return exercises that are slightly more difficult than the student's current understanding level (Cornelisz & van Klaveren, 2018) or items/learning activities that students need additional practices (Wang, 2014;Wongwatkit et al, 2020;You et al, 2019) Virtual Reality: Customize learning path with which students can interact constantly (Bhattacharjee et al, 20...…”

Section: Provide Multiple Means Of Representationmentioning

confidence: 99%

Integrating instructional designs of personalized learning through the lens of universal design for learning

Zhang

Carter

Basham

et al. 2022

Computer Assisted Learning

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Background: Personalized learning (PL), conceptualized as an education innovation that tailors learning to meet diverse student needs, has drawn increased attention from different fields of study, such as education, learning sciences, and computer science. Regardless, there is a lack of a comprehensive understanding of PL instructional designs supported by technology.Objectives: This systematic literature review aimed to provide an empirical integration of PL designs and implementation across disciplines through the lens of the universal design for learning (UDL) framework. As an instructional framework that guides the design to embrace learner variability, UDL holds the potential to provide foundational considerations for instructional design components of PL.Methods: We used four databases including ERIC, OmniFile Full Text Select, Academic Search Complete, and Web of Science to search empirical studies investigating technology-supported PL in PK-12 school-based settings. In total, 61 studies published between 2006 and 2020 were included in the review. We analysed PL design and implementation features and aligned these features to the UDL framework.Results and Conclusions: Our results indicated that current empirical PL design features were widely mapped onto the UDL framework. Most current PL studies investigated segmented aspects such as student attributes (e.g., interest, motivation, self-regulation) and instructional practices (e.g., facilitating goal setting) that could contribute to PL design. Rarely did studies investigate how PL was operationalized in a system integrating various design components that consider learner characteristics, instructional support, and contextual implementation factors.Implications: The analysis of alignment between PL designs within the UDL framework can serve as a starting point for stakeholders to take a more holistic approach to designing PL experiences for all learners.

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“…Next to technological developments, novel educational approaches are readily available to further enhance industrial training. Recently the educational technological research community highlighted technology-enhanced adaptive learning to be a key learning paradigm (Kenny & Pahl, 2009;Wang et al, 2020;Xie et al, 2019) as it offers the opportunity to first determine user strengths and weaknesses and consequently adapt the amount of instruction the user needs to receive (Martinetti et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Ready, trainer … one*! discovering the entanglement of adaptive learning with virtual reality in industrial training: a case study

Abbas

Martinetti

Nizamis

et al. 2021

Interactive Learning Environments

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In response to the industrial world becoming more complex and the recent social distancing caused by the COVID-19 outbreak, emerging technologies such as Virtual Reality (VR) are gaining importance for industrial training. The novelty, however, does not lie in the sole use of VR-based technology but rather in its adaptive and flexible nature. This paper explores the synergy between VR environments and adaptivebased learning and tests the proposed approach in the railway sector. An iterative co-design approach is adopted to develop a VR-based training system for educating train conductors. The developed system is validated with ten conductors, where their learning preference, learning outcome, and learning performance were assessed. The results show an increase in individual motivation and perceived usefulness for the developed VR-based training system, demonstrating a higher learning preference, in comparison to the currently used physical simulator. Similarly, the results outline a knowledge gain in two out of six key knowledge subjects for conductor education and indicate that time improvements per exercise are needed to meet organizational performance goals. Consequently, this research presents an attractive alternative to costly and product-specific physical simulators and offers three strategic managerial implications opening new opportunities for using VR in developing learning training programmes.

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When adaptive learning is effective learning: comparison of an adaptive learning system to teacher-led instruction

Cited by 97 publications

References 20 publications

Learning Performance in Adaptive Learning Systems: A Case Study of Web Programming Learning Recommendations

Learning Performance in Adaptive Learning Systems: A Case Study of Web Programming Learning Recommendations

Integrating instructional designs of personalized learning through the lens of universal design for learning

Ready, trainer … one*! discovering the entanglement of adaptive learning with virtual reality in industrial training: a case study

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