Mobile Learning - The Future Already Behind Us A Review and Analysis of the Bigger Picture

被引:0
|
作者
Traxler, John [1 ]
机构
[1] Wolverhampton Univ, Learning Lab, Wolverhampton WV1 1DJ, W Midlands, England
关键词
component; development; globalisation; future; mobile learning;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile learning as a concept and as a community are now over ten years old. They have been successful in many respects working within educational institutions to extend the reach of education, to enrich its experience, to motivate learners and to extend educational theory. The near universal ownership of mobiles and increased global awareness of their potential dramatically alters the dynamics of the mobile learning community.
引用
收藏
页码:7 / 9
页数:3
相关论文
共 50 条
  • [41] Quality review and content analysis of liver complications mobile apps in Iran: A statistical and machine learning approach
    Kermani, Farzaneh
    Mahmoodi, Mahdi
    Nasiri, Mohammad Reza
    Orooji, Azam
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2025, 197
  • [42] Effects of Smartphone-Based Mobile Learning in Nursing Education: A Systematic Review and Meta-analysis
    Kim, Ju Hee
    Park, Hanjong
    ASIAN NURSING RESEARCH, 2019, 13 (01) : 20 - 29
  • [43] Pressure injury image analysis with machine learning techniques: A systematic review on previous and possible future methods
    Zahia, Sofia
    Garcia Zapirain, Maria Begona
    Sevillano, Xavier
    Gonzalez, Alejandro
    Kim, Paul J.
    Elmaghraby, Adel
    ARTIFICIAL INTELLIGENCE IN MEDICINE, 2020, 102
  • [44] Exploring the Landscape of Machine Learning Applications in Neurosurgery: A Bibliometric Analysis and Narrative Review of Trends and Future Directions
    Levy, Adam S.
    Bhatia, Shovan
    Merenzon, Martin A.
    Andryski, Allie L.
    Rivera, Cameron A.
    Daggubati, Lekhaj C.
    Di, Long
    Shah, Ashish H.
    Komotar, Ricardo J.
    Ivan, Michael E.
    WORLD NEUROSURGERY, 2024, 181 : 108 - 115
  • [45] A Comprehensive Review of Machine Learning Approaches for Anomaly Detection in Smart Homes: Experimental Analysis and Future Directions
    Rahman, Md Motiur
    Gupta, Deepti
    Bhatt, Smriti
    Shokouhmand, Shiva
    Faezipour, Miad
    FUTURE INTERNET, 2024, 16 (04)
  • [46] Machine learning applications in imaging analysis for patients with pituitary tumors: a review of the current literature and future directions
    Ashirbani Saha
    Samantha Tso
    Jessica Rabski
    Alireza Sadeghian
    Michael D. Cusimano
    Pituitary, 2020, 23 : 273 - 293
  • [47] Machine learning applications in imaging analysis for patients with pituitary tumors: a review of the current literature and future directions
    Saha, Ashirbani
    Tso, Samantha
    Rabski, Jessica
    Sadeghian, Alireza
    Cusimano, Michael D.
    PITUITARY, 2020, 23 (03) : 273 - 293
  • [48] Critical review on data-driven approaches for learning from accidents: Comparative analysis and future research
    Niu, Yi
    Fan, Yunxiao
    Ju, Xing
    SAFETY SCIENCE, 2024, 171
  • [49] Unified theory of acceptance and use of technology (UTAUT) in mobile learning adoption : Systematic literature review and bibliometric analysis
    Aytekin, Alper
    Ozkose, Hakan
    Ayaz, Ahmet
    COLLNET JOURNAL OF SCIENTOMETRICS AND INFORMATION MANAGEMENT, 2022, 16 (01) : 75 - 116
  • [50] Mobile Apps to Improve Brace-Wearing Compliance in Patients with Idiopathic Scoliosis: A Quality Analysis, Functionality Review and Future Directions
    Cho, Han Eol
    Jang, Chan Woong
    Cho, Sung Rae
    Choi, Won Ah
    Park, Jung Hyun
    JOURNAL OF CLINICAL MEDICINE, 2023, 12 (05)