Learning Analytics Based on Wearable Devices: A Systematic Literature Review From 2011 to 2021

被引:14
作者
Liu, Zhi [1 ]
Ren, Yupei [1 ]
Kong, Xi [1 ]
Liu, Sannyuya [1 ,2 ]
机构
[1] Cent China Normal Univ, Natl Engn Lab Educ Big Data, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
[2] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
wearable devices; learning analytics; systematic review; physiological signals; COGNITIVE LOAD; SUSTAINED ATTENTION; EDUCATION; EMOTIONS; MODEL; ENGAGEMENT; INTERNET; OPPORTUNITIES; CREATIVITY; EXPRESSION;
D O I
10.1177/07356331211064780
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Wearable devices are an emerging technological tool in the field of learning analytics. With the help of wearable technologies, an increasing number of scholars have a strong interest in studying the associations between student data and learning outcomes in different learning environments. This systematic review examines 120 articles published between 2011 and 2021, exploring current research on learning analytics based on wearable devices in detail from both descriptive and content analysis. The descriptive analysis reviewed the included literature in five dimensions: publication times of the reviewed literature, wearable devices and data types used in studies, stakeholders, objectives, and methods involved in the analysis procedure. The content analysis aims to examine the literature covered in terms of three categorical domains of educational objectives: cognitive, affective, and behavioral, to investigate the practical applications and potential issues of learning analytics based on wearable devices. After that, based on the overall research content of the reviewed literature, a framework for learning analytics based on wearable devices is present, and its application process is summarized and analyzed for the reference of related researchers. At last, we summarize the limitations of existing studies and present several recommendations to further promote research and development in this field.
引用
收藏
页码:1514 / 1557
页数:44
相关论文
共 162 条
[1]   Biosignals reflect pair-dynamics in collaborative work: EDA and ECG study of pair-programming in a classroom environment [J].
Ahonen, Lauri ;
Cowley, Benjamin Ultan ;
Hellas, Arto ;
Puolamaki, Kai .
SCIENTIFIC REPORTS, 2018, 8
[3]   Innovation in physical education: Teachers' perspectives on readiness for wearable technology integration [J].
Almusawi, Hashem A. ;
Durugbo, Christopher M. ;
Bugawa, Afaf M. .
COMPUTERS & EDUCATION, 2021, 167
[4]  
Anderson J. R., 2005, Cognitive psychology and its implications
[5]   Biosensor Real-Time Affective Analytics in Virtual and Mixed Reality Medical Education Serious Games: Cohort Study [J].
Antoniou, Panagiotis E. ;
Arfaras, George ;
Pandria, Niki ;
Athanasiou, Alkinoos ;
Ntakakis, George ;
Babatsikos, Emmanouil ;
Nigdelis, Vasilis ;
Bamidis, Panagiotis .
JMIR SERIOUS GAMES, 2020, 8 (03)
[6]   Reducing Anxiety and Improving Academic Performance Through a Biofeedback Relaxation Training Program [J].
Aritzeta, Aitor ;
Soroa, Goretti ;
Balluerka, Nekane ;
Muela, Alexander ;
Gorostiaga, Arantxa ;
Aliri, Jone .
APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK, 2017, 42 (03) :193-202
[7]   Wearable Learning: Multiplayer Embodied Games for Math [J].
Arroyo, Ivon ;
Micciollo, Matthew ;
Casano, Jonathan ;
Ottmar, Erin ;
Hulse, Taylyn ;
Mercedes Rodrigo, Ma .
CHI PLAY'17: PROCEEDINGS OF THE ANNUAL SYMPOSIUM ON COMPUTER-HUMAN INTERACTION IN PLAY, 2017, :205-216
[8]  
Association I. Management, 2018, Wearable Technologies: Concepts, Methodologies, Tools, and Applications, P403, DOI DOI 10.4018/978-1-5225-5484-4.CH019
[9]   LSTM-Based Emotion Detection Using Physiological Signals: IoT Framework for Healthcare and Distance Learning in COVID-19 [J].
Awais, Muhammad ;
Raza, Mohsin ;
Singh, Nishant ;
Bashir, Kiran ;
Manzoor, Umar ;
Ul Islam, Saif ;
Rodrigues, Joel J. P. C. .
IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (23) :16863-16871
[10]   Systematic reviews in the social sciences. A practical guide. [J].
Beelmann, Andreas .
EUROPEAN PSYCHOLOGIST, 2006, 11 (03) :244-245