Mobile Learning In Higher Education Research Articles

Understanding mature students' intention to use mobile learning in higher education: integrating personality traits and UTAUT

PurposeThis study aims to provide new insights into the relationship between individual characteristics, particularly personality traits and mature students' intention to use (ITU) mobile learning (m-learning).Design/methodology/approachThe research model was constructed by integrating the Big Five personality traits into the unified theory of acceptance and use of technology (UTAUT) model. The data were collected from mature students at a university research center in Macau. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the data and test the proposed hypotheses.FindingsThe results reveal that personality traits play a significant role in determining mature students' ITU m-learning technology. In particular, social influence (SI) mediates the relationship between agreeableness (AGB) and ITU.Originality/valueThis study examines how personality traits collectively influence mature students' receptiveness and intentions toward m-learning. As mature learners' motivations and preferences remain underexplored, insights into trait-technology links could address current gaps and optimize mobile educational support tailored to their distinct characteristics and needs.

Tutorials and mobile learning in higher education: Enhancing and accessibility

This comprehensive paper delves into two vital facets of contemporary higher education. The first segment investigates the transformative force of mobile learning (m-learning), elucidating its far-reaching impact on the educational landscape. Offering unprecedented flexibility and accessibility, m-learning redefines the dynamics between students and educators. The exploration navigates through potential benefits, challenges, and broader implications, providing a nuanced understanding of the evolving landscape of higher education in the digital age. The second segment focuses on the impact of active teaching in a first-year class at the National Engineering School of Carthage (ENICarthage) in Tunisia. Active teaching, recognized for engaging students in the learning process, is scrutinized for its effectiveness in enhancing theoretical understanding and graded assignment performance. This research introduces a dynamic dimension by incorporating mobile learning and tutorials as integral components of active teaching strategies. With its technological leverage, mobile learning aims to enhance student engagement, while advanced tutorials feature simulation functionality for an immersive learning experience. Through statistical analysis, the paper contributes to a nuanced comprehension of the positive influence of active teaching on academic achievements, offering practical insights into the application of active teaching methods and their potential benefits for enhancing student learning outcomes. This synthesis thus presents a holistic view of the dynamic interplay between mobile learning and active teaching in shaping the contemporary higher education landscape.

COMPREHENSIVE SYSTEMATIC REVIEW ON MOBILE LEARNING IN HIGHER EDUCATION

As mobile technologies continue to make their way into every part of modern life, it is important to systematically study the literature to investigate the many different aspects of M-learning in higher education. The primary aim of this study is to investigate the prevailing trends in mobile learning (M-learning) within the higher education sector, specifically focusing on the period from 2021 to 2023. The intention is to furnish fellow researchers with up-to-date insights into the current landscape of M-learning trends. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework provide Systematic Literature Review (SLR) methodological rigor and quality assurance. Using two digital libraries, SCOPUS and Web of Science, 29 articles were ultimately analyzed. This systematic literature review discusses the mobile learning trend in 4 themes: Acceptance and Adoption of Mobile Learning, factors Influencing Mobile Learning, Perceptions and Attitudes towards Mobile Learning, and effectiveness of mobile learning. This systematic literature review on mobile learning in higher education presents that it is becoming more important. It sheds light on what makes people accept M-learning, how perceptions play a part, and how M-learning affects academic performance. Suggestions for future study in M-learning are to focus on new technologies, making it easier for students with disabilities to use, cultural factors, and environmental effects.

Discovering the synergies among information literacy and mobile learning in higher education

This research aims at exploring the synergies and relationships between information literacy and mobile learning domains in Higher Education environments. The method is based on a narrative literature review of available articles in English (2006-2022) and one selection of the most relevant items using qualitative content analysis, to discover the main topics and their relationships. Results confirm that information literacy and m-learning are close and interrelated domains. Mobile technologies and academic libraries perform an intermediating role in those relationships. With the support of mobile technologies, the progressive integration of information literacy and mobile learning may lead the academic library to experience and channel an enhanced service. The greatest challenge consists in adapting the concepts and behaviors informational and pedagogical to a technology that evolves relentlessly but, in any event, ought to point to individual and community needs. The academic library is a pivotal entity in channeling the progress of IL and mobile learning.

Influence and scope of mobile learning in higher education: A systematic literature review

Due to the soaring progression in portable innovations and mobile technology, the popularity of mobile phones has expanded dramatically, which has led to the widespread adoption of mobile gadgets by almost every age group, especially the youth. The apparent consequence is embracing mobile phones in teaching-learning processes. Researchers have been inclined to study the potential and impact of incorporating mobile devices into the education system in recent years. Many studies have been conducted to explore the viability of integrating mobile gadgets into the higher education system. However, only a few works have addressed the realm from the perspective of the Indian higher education system. The present work employs the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework and endeavours to contribute to the literature by exercising a systematic literature review of the open-access literary works carried out from the standpoint of India, especially the Uttarakhand province. The essential keywords, inclusion/exclusion criteria, and research questions addressing the cruxes of the desired investigation are contemplated and designed first. The articles are then populated from the leading academic databases, general web resources, and government reports. The PRISMA guidelines are followed to filter out articles satisfying the adopted criteria. The final shortlisted articles are then rigorously studied to develop insights and to answer the framed questions. The observations signalize the need to frame effective policies and address the hurdles to optimize the usage and impact of mobile learning in Indian higher education, including the education system of Uttarakhand.

Mobile Learning in Higher Education: A Systematic Literature Review

Mobile learning (M-Learning) has become a popular and effective method of education that leverages the ubiquity of mobile devices. M-Learning has digitally transformed the process of teaching and learning. It has tremendous potential to empower all sections of society through education and training. This study presents a systematic literature review of M-Learning. The articles were retrieved from Scopus and Web of Science databases. After applying inclusion and exclusion criteria, a final selection of 161 articles published between 2016 and 2022 was included in the review. To analyze the articles, the researchers employed the TCCM (Theory, Context, Characteristics, Methods) framework, which facilitated addressing the research questions. This review identified various theories, such as behaviorism, constructivism, cognitivism, situated learning, problem-based learning, context awareness learning, socio-cultural theory, collaborative learning, conversational learning, lifelong learning, informal learning, activity theory, connectivism, navigation, and location-based learning, that are used to support and guide the implementation of M-Learning. In terms of context, developing countries contributed to 70.8% of the studies, while developed countries contributed to 29.1%. Further, a majority of the studies, 93%, involved students followed by faculty members and only two studies involved staff from higher education management. A total of 19 unique characteristic factors have been identified, such as personal, intention, attitude, usage, utility, ease of use, learnability, social, technological, pedagogical, anxiety, enjoyment, accessibility, knowledge, experience, trust, price, and habit. A quantitative research design was used in 90% of the studies, followed by mixed methods research design in 7% of the studies, and qualitative research design in only 3% of the studies. Further, this article synthesizes previous research findings and highlights gaps for future research. Overall, this review contributes to the understanding and advancement of M-Learning as a valuable educational platform.

Novel Impact Model for Mobile Learning Adoption in Higher Education

In successful mobile learning (ML) integration, factors associated with live-ware, software, and infrastructure are important. The main objective of this study is to investigate and model the influencing factors for learners and teachers at once to adopt ML in higher education. The proposed model consists of five impact factors: teacher, learner, mobile devices, ML tools, ML contents, communication technologies, and higher education institutes. Then the proposed               model was implemented using a modified Moodle mobile application and evaluated using                      60 teachers and 60 learners attached to the University of Kelaniya, Sri Lanka in 2021. According   to the experimental research design approach, the proposed impact model was assessed as pre-test and post-test surveys using seven questionnaires. According to the Pearson correlation coefficient test, the most significant factor for learners and teachers to adopt ML is the mobile device. Learning content and communication technology were elected as the second most significant adoption factors for teachers and learners consecutively. However, higher correlation values were obtained for all factors denoting that they are greatly influenced the participant to adopt ML. The significant influencing factor of each impact factor was also investigated. In conclusion, it was recommended that featured smart devices, quality learning content, user-satisfied communication technology, academic enriched ML tools and higher education institutes with sound educational facilities are crucial for the university community to adopt ML in higher education. These findings help design academic community acceptable ML environments for higher education context.

Mobile Learning in Higher Education: Insights from a Bibliometric Analysis of the Body of Knowledge

Mobile learning is a research domain that has gained wide prominence in contemporary Information and Communication Technology (ICT) literature. As a result, there is a need for periodic and extensive review studies to keep abreast with the latest scholarly trends. Nevertheless, review studies on mobile learning, particularly in the post-COVID-19 era, are still limited. This article presents a bibliometric overview of mobile learning in higher education literature published between 1 January 2002 and 15 November 2022. The methodology used in this research is enshrined in the core principles of scientometrics forming the basis of the bibliometric approach utilised in the study. The articles for analysis were extracted from the Web of Science (WoS) database and analysed according to defined bibliometric indicators. The VOSviewer software tool (version 1.6.18) was employed in mapping the bibliometric articles. The findings of this research reveal that mobile learning scholarship has grown consistently in the period of analysis covered in this study. It was observed in the bibliometric analysis that the most productive countries in mobile learning in higher education are the USA and China. The most influential author is M.A. Almaiah. In the recent past, universities in the Middle East have demonstrated an excellent growth projectile in mobile learning research. Education and Information Technologies produced most content on mobile learning research demonstrating its stature as a leading publication platform advancing scholarly debate on mobile learning relating to context, augmented reality, COVID-19, continuance intention and knowledge. From the foregoing, possible future research avenues are discussed.

Mobile Learning in Higher Education: A Mixed Research Synthesis

Bu araştırmanın amacı, Türkiye’de yükseköğretim düzeyinde mobil öğrenmeye yönelik yayınlanmış bilimsel makalelerin eğilimlerini incelemek ve sonuçlarını sentezlemektir. Araştırmada, karma araştırma sentezi yöntemi benimsenmiş ve 2010-2020 yılları arasında yayınlanan 80 makalenin sonuçları sentezlenmiştir. Öne çıkan sonuçlardan bazıları şunlardır: Çalışmalarda en fazla nicel araştırma yöntemi ve tarama deseni tercih edilmiştir. Örneklem olarak en sık öğrencilerle çalışılmıştır. Ölçek, en fazla kullanılan veri toplama aracı, t testi en çok başvurulan veri analizi yöntemidir. Sentezlenen makaleler; mobil öğrenmeye yönelik görüşler, mobil öğrenmeye hazırbulunuşluk, mobil öğrenmenin avantaj ve sınırlılıkları, mobil öğrenmenin kullanım yerleri, mobil öğrenmeye yönelik tutum, mobil öğrenmede yeni teknolojiler, mobil öğrenmeyle ilgili içerik analizi ve meta-analiz, mobil öğrenmenin akademik başarı, tutum ve beceriler üzerindeki etkisi, mobil öğrenmeye yönelik ölçekler ve yabancı dil öğretiminde mobil öğrenme başlıkları altında incelenmiştir. Sonuçlara göre mobil öğrenmeye yönelik görüş ve tutumlar genel olarak olumludur. Mobil öğrenme öğrenciye bağımsızlık, bireysel öğrenme ve özgürlük sağladığı için etkili bulunmaktadır. Mobil öğrenmenin öğrenci motivasyonunu ve performansını arttırdığı düşünülmektedir.

Factors That Influence Mobile Learning among University Students in Romania

During the pandemic years, universities worldwide adopted online teaching on a large scale. Besides desktop systems or laptops, many students also use smartphones for online learning. In our paper, we propose a hybrid theoretical model to analyze the continuance intention to use mobile learning in higher education. The scientific demarche is carried out from different perspectives opened by the models and theories integrated in a unitary approach. In addition to the main constructs taken from the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the research model was enriched with new capabilities by considering the Motivational Model (MM), Flow Theory (FT) and the Social Cognitive Theory (SCT). The research model was applied to the Romanian higher education environment and proved that perceived usefulness (PU), habit (HB), perceived skill (PS), and self-efficacy (SE) directly influence the continuance intention to use (CU) smartphones in higher education. Further, performance expectancy (PFE), intrinsic motivation (IM), perceived ease of use (PEOU), and perceived enjoyment (PE) indirectly influence the continuance intention to use (CU). We presented our results according to top studies on the critical challenges and factors influencing smart mobile learning success usage during the COVID-19 pandemic. Thus, we found that Romanian universities provide excellent IT infrastructure and top management support and that creating habits of using m-learning in the context of university classes will strengthen the university culture. The conclusions of the undertaken research represent a starting point in the diversification and flexibility of educational processes in Romanian universities.

Educators’ Utilizing One-Stop Mobile Learning Approach amid Global Health Emergencies: Do Technology Acceptance Determinants Matter?

In July 2022, the World Health Organization (WHO) declared the rapidly spreading monkeypox outbreak a global health emergency; in the future, this may cause the closure of higher education institutions and a shift toward digital learning. As before, specifically in March 2020, the WHO expressed that COVID-19 is a worldwide pandemic. This transformation was accompanied by the widespread adoption of mobiles and their applications in learning with organised or non-organised forms. Although many articles have recorded the importance and effectiveness of mobile learning in higher education, other articles have indicated the weak utilisation of mobile learning amid the COVID-19 pandemic, especially by university educators (UEs). In addition, these articles often focus on the opportunities, challenges, and weaknesses of mobile learning amid COVID-19, but few studies have handled the acceptance of the UEs to adopt a mobile learning approach amid COVID-19 by the unified theory of acceptance and use of technology (UTAUT). This article’s main contribution is extending the (UTAUT) model in context and reviewing the acceptance of the adoption of mobiles and their applications in education as an approach amid global health emergencies, i.e., COVID-19 and monkeypox. The data were gathered from university educators (N = 392) in Saudi Arabia. The hypotheses were evaluated with data that were analysed using structural equation modelling (SEM). The results demonstrated that six of the eight hypotheses had high and significant effects on behaviour intention (performance expectancy (PE), effort expectancy (EF), social influence (SI), facilitating conditions (FC), self-efficacy (SE), and users’ awareness (UA)). Two of the eight factors have insignificant or negative impacts on behaviour intention (users’ perceptions (UP) and technology challenges (TC)), which need an additional review by policymakers, practitioners, mobile learning providers, and investigators looking to develop efficient strategies concerning mobile learning.

Unpacking Mobile Learning in Higher Vocational Education During the COVID-19 Pandemic

Mobile learning in higher education has become more popular than ever during the COVID-19 pandemic. However, the presence of mobile learning in Chinese higher vocational education is unexplored. Therefore, the aim of this research is to extend the unified theory of acceptance and use of technology (UTAUT) by incorporating three sub-dimensions of self-efficacy for measuring students' acceptance of mobile learning in Chinese higher vocational education. A total sample of 900 students from higher vocational colleges were selected to participate in this study and their responses were analysed using structural equation modelling to validate the extended UTAUT. The results provide significant evidence of the sub-dimensions of self-efficacy and confirm the validity of extended UTAUT. The results also show that students' effort and performance expectancies, social influence and facilitating condition were directly affected by their self-efficacies to use mobile learning.

Global Trends on Mobile Learning in Higher Education: A Bibliometric Analysis (2002–2022)

This study explores the research landscape of mobile learning in the context of higher education (MLHE) by conducting a comprehensive bibliometric analysis over the years. A total of 2477 papers published in peer-reviewed journals and conferences up to May 2022 were retrieved from the Scopus database. The results revealed an increase in MLHE research over time with a peak in 2021. The first paper was published in 2002, indicating the beginning of the field. The works of J. Gikas and M. M. Grant, L. F. Motiwalla, and J. Cheon et al. stand out as the most cited articles among the analyzed documents. T. Cochrane, F. J. García-Peñalvo, and H. Farley are the most prolific authors. ACM International Conference Proceeding Series, International Journal of Interactive Mobile Technologies, and International Journal of Mobile Learning and Organisation are the most productive sources. University of Salamanca, Science University of Malaysia (Universiti Sains Malaysia), and the University of Southern Queensland are the most active institutions. China, the US, and the UK are the most relevant countries. Keywords such as “mobile learning”, “m-learning”, “higher education”, “e-learning”, and “mobile devices” remain the trending keywords in this area. This review offers a comprehensive overview of scientific production and the future direction of the field.

The integrated social cognitive theory with the TAM model: The impact of M-learning in King Saud University art education.

Technology in higher education now includes a substantial amount of mobile learning (M-learning). M-learning also enables students to use the internet and technology for research, teamwork, and idea sharing. Additionally, in order to use M-learning systems, both students and teachers must accept M-learning. However, not enough research has been done in Saudi Arabia to determine how satisfied students are with their real use of mobile learning for educational purposes. As a result, the current study intends to investigate students' behavioral intentions to utilize mobile learning, their happiness with the technology, as well as their impressions of how they actually use mobile learning systems. Therefore, this study aimed to develop a new model by integrating social cognition theory and the technology acceptance model to better understand the elements that influence the adoption of mobile learning in higher education (TAM). The majority of the information was gathered through a survey, with 412 university students' randomly assigned questionnaires. The data analysis tools utilized were SPSS and Smart-PLS3.3.3. The studies proposed research model could, according to the study's findings, account for 52.5% of the variation in how mobile learning systems were actually used. This information is crucial for understanding how social and educational technology factors affect the actual use of mobile learning systems. With only two hypotheses being rejected, this study created a new model that supported 16 of them. The findings indicated a beneficial relationship between 10 social and educational technology elements. The findings also indicated a favorable impact on students' behavioral intentions to use and student happiness, which favorably impacts the actual use of M-learning in higher education. In order to improve students' academic performance via mobile learning, social cognitive theory and the TAM model are combined as a consequence of the study's empirical results. Therefore, we encourage students to collaborate with their colleagues at higher education institutions and use M-learning in their classrooms.

Investigating lecturers’ reasons for adoption of mobile learning in higher education: A case study


 
 
 The usage of Mobile Learning (M-learning) has grown among Institutes of Higher Learning worldwide as mobile technologies benefit teaching and learning. Despite this interest, there is a lack of M-learning research in formal educational contexts and the reasons for lecturers to adopt M-learning in a Singapore private education institute have been limited. Furthermore, the Teaching and Learning Division (TLD) of the institution which looks after the professional development of lecturers and sponsors innovative technology-mediated learning initiatives like M-learning is keen to find out how lecturers can be supported to encourage a greater usage of M-learning. After interviewing 10 lecturers, the research found that the following five reasons influence lecturers’ adoption of M-learning from most important to the least: Usefulness in Teaching and Learning, Barriers to using M-Learning, Ease of use of mobile technology, Students’ Motivation and Service quality of the M-learning systems. From this, TLD can identify and develop strategies to support the successful integration of M-learning. The five support aspects considered when implementing M-learning are found to be the following in descending order of importance: Professional Development, Social, Organisational, Technical and Advanced features to support teaching and learning. This research has clarified the existing literature in M-learning especially in formal learning contexts where learning is intentional and recognises the role that lecturers play in the future adoption of M-learning.
 
 

Lecturers’ Perspectives on Mobile Learning in Higher Education: Experiences and Implementation Barriers

This paper reports the experiences of university lecturers towards mobile learning from two points of view: (i) lecturers’ needs and experiences in relation to mobile learning design and implementation, and (ii) possible barriers to their adoption in higher education classrooms. The findings from a qualitative case study that conducted semi-structured interviews with 12 lecturers from a developed and developing country contexts revealed; the need for strong commitment from institutional leadership, presence of an institutional and national mobile learning policy, a culture of innovation and willingness to revise the traditional curriculum to incorporate the new mobile pedagogies.

Effects and Perceptions of Mobile Learning in Higher Education

Objectives: This study aimed to investigate the effect of mobile learning on students’ achievement in the grammar of the Arabic language, and their attitude towards the use of mobile learning. Methods/Analysis: The study was conducted using a quasi-experimental design, case study. The sample comprised 170 students, divided into two groups: an experimental group (n = 87) and a control group (n = 83). An achievement test and a questionnaire were used to collect data, which was analyzed using SPSS. Findings: The findings revealed statistically significant differences between the two groups, with the experimental group showing better scholastic achievement on the test. The results also show that the students of the experimental group were more positive towards mobile learning. Novel contribution: The study recommends further studies on the use of mobile learning in universities and schools. It is necessary to emphasize and focus on further studies on the use of mobile learning within universities and schools to confirm and provide evidence of the significance of mobile learning in terms of facilitating, promoting, and enhancing the educational process. Doi: 10.28991/ESJ-2022-SIED-06 Full Text: PDF

Mobile Learning in Higher Education through Covid 19 Epidemic (Review)

Mobile Learning in Higher Education through Covid 19 Epidemic (Review)

When industry meets academia

This presentation focuses on a transdisciplinary approach to innovative and collaborative learning practices driven by technology. It highlights two salient elements associated with industry practices and processes in relation to learning and educational contexts: empowerment of individuals and communities of practice through technology, and a broader consideration of industrial approaches to the concept of learning and teaching enhanced within a digital environment.
 More precisely, this presentation will feature some of the key theoretical frameworks used in three different settings of learning and teaching in France with regards to the life-long learning approach thanks to Social and Emotional Learning (SEL) (WEF, 2016). It will also discuss the positive effect of the Internet and its affordances (Southerton & Taylor, 2020) on reducing the differences between theoretical and applied knowledge via professional-focused communities (Danvers, 2003). Thus, it will briefly explain that spatial and cognitive learning proximities (Lave & Wenger 1991; Fruchter, 2001) can be reduced by virtue of technology (Anders, 2016; Antonczak, 2019; Glazewski & Hmelo-Silver, 2019) and that ‘computer-supported collaborative learning’ methods can facilitate social and shared problem-solving (Sawyer, 2005; Levallet & Chan, 2018; Presicce et al., 2020) without the ‘restriction of time and place’ (Cheng et al., 2019, 489). Additionally, it will point out some aspects of problem-solving through ‘emancipatory learning and social action’ (Merriam, 2001, 9) through the use of ‘actual’ content and ‘actionable feedback’ (Woods & Hennessy, 2019) enhanced by digital tools and tactics.
 Next, it will focus on three case studies by concisely presenting key specifics for each of the courses, including the various digital tools used and followed by some quick interim reflections.
 Then it will summarise the challenges and the barriers encountered across the different practices such as virtual delivery, the size of the students' groups and some connectivity considerations. It will be followed by the principal advantages and opportunities, like the professionalisation dimension through interactive and authentic learning enhanced by affordances. And it will conclude with some managerial recommendations as experiential and practical methods (knowledge codification) thanks to industry-based teaching supported by digital technologies.
 The presentation will close with the overall conclusion in relation to digital technology and some of the key 21st-century career skills. In general, the findings will be of interest to academics, practitioners and policymakers. The added value of this transdisciplinary investigation is that it improves research on collaborative innovation and collective knowledge by creating a bridge between the fields of Education and Business.
  
 Bibliography
 Anders, A. (2016). Team communication platforms and emergent social collaboration practices. International Journal of Business Communication, 53(2), pp. 224-261.
 Ananiadou, K. & M. Claro (2009). 21st Century Skills and Competences for New Millennium Learners in OECD Countries, OECD Education Working Papers, No. 41, OECD Publishing.
 Antonczak, L. (2019). Scaling-up collaborative practices through mobile technology. The 25th International Conference on Engineering/International Technology Management Conference (ICE/ITMC), June 17-19, Nice.
 Askay, D. A. & Spivack, A. J. (2010). The multidimensional role of trust in enabling creativity within virtual communities of practice: A theoretical model integrating swift, knowledge-based, institution-based, and organizational trust. In 43rd Hawaii International Conference on System Sciences, Hawaii, pp. 1-10.
 Cairns, L. (2000). The process/outcome approach to becoming a capable organization. In Australian Capability Network Conference, Sydney, 1-14.  
 Cheng, E. W., Chu, S. K., & Ma, C. S. (2019). Students’ intentions to use PBWorks: a factor-based PLS-SEM approach. Information and Learning Sciences, 120(7/8), 489-504.
 Cochrane, T., Antonczak, L., Guinibert, M., Mulrennan, D., Rive, V., & Withell, A. (2017). A framework for designing transformative mobile learning. In Mobile Learning in Higher Education in the Asia-Pacific Region ( 25-43). Springer, Singapore.
 Danvers, J. (2003). Towards a radical pedagogy: Provisional notes on learning and teaching in art & design. International Journal of Art & Design Education, 22(1), 47-57.
 Dewey, J. (1991). Logic: The theory of inquiry. In J. A. Boydston (Ed.), John Dewey: The Later Works, 1925–1953, Vol. 12 (1-5). Carbondale, IL: SIU Press. [Originally published in 1938]
 Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., & Sicilia, N. (2018). Blended learning: the new normal and emerging technologies. International Journal of Educational Technology in Higher Education, 15(1), 1-16.
 Fruchter, R. (2001). Dimensions of teamwork education. International Journal of Engineering Education, 17(4/5), 426-430.
 Glazewski, K. D., & Hmelo-Silver, C. E. (2019). Scaffolding and supporting the use of information for ambitious learning practices. Information and Learning Sciences, 120(1/2), 39-58.
 Hase, S. & Kenyon, C. (2007). Heutagogy: A child of complexity theory. Complicity: An International Journal of Complexity and Education, 4(1), 111-119.
 Lave, J. & Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press.
 Levallet, N., & Chan, Y. E. (2018). Role of Digital Capabilities in Unleashing the Power of Managerial Improvisation. MIS Quarterly Executive, 17(1), 1-21.
 Lewin, K. (1947). Group decision and social change. Readings in Social Psychology, 3(1), 197-211.
 McKenney, S., & Reeves, T. C. (2013). Systematic review of design-based research progress: Is a little knowledge a dangerous thing?. Educational Researcher, 42(2), 97-100.
 Makri, S., Ravem, M., & McKay, D. (2017). After serendipity strikes: Creating value from encountered information. Proceedings of the Association for Information Science and Technology, 54(1), 279-288.
 Mascheroni, G., & Vincent, J. (2016). Perpetual contact as a communicative affordance: Opportunities, constraints, and emotions. Mobile Media & Communication, 4(3), 310-326.
 Merriam, S. B. (2001). Andragogy and self-directed learning: Pillars of adult learning theory. New Directions for Adult and Continuing Education, 89, 3-13.
 Pont, B. (2013). Learning Standards, Teaching Standards and Standards for School Principals: A Comparative Study. Rapport no. EDU/WKP(2013)14. Centre of Study for Policies and Practices in Education (CEPPE). Retrieved from: http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=EDU/WKP(2013)14&docLanguage=En (accessed December 31, 2020).
 Presicce, C., Jain, R., Rodeghiero, C., Gabaree, L. E., & Rusk, N. (2020). WeScratch: an inclusive, playful and collaborative approach to creative learning online. Information and Learning Sciences, 121(7/8), 695-704.
 Reeves, T. C. (2005). Design-based research in educational technology: Progress made, challenges remain. Educational Technology, 45(1), 48-52.
 Southerton, C., & Taylor, E. (2020). Habitual disclosure: Routine, affordance, and the ethics of young peoples social media data surveillance. Social Media+ Society, 6(2), https://doi.org/10.1177/2056305120915612

TRENDS AND PROSPECTS OF MOBILE LEARNING TECHNOLOGY IN EDUCATION

The rapid development of digital technologies has led to the transformation and modernization of the educational process, becoming the basis for significant changes in traditional teaching methods. Today, what is happening in the world – the pandemic – puts at the forefront a fundamental study of the issue of transferring education to digital format. The aim of this study is to present the results of research in the field of application of new technologies in higher education with special attention to mobile learning as a modern innovative approach and to determine the current situation and prospects for the application of mobile technologies in teaching. The authors take mobile learning as a promising vector of digital pedagogy, describe the advantages of using mobile learning technologies in the organization of the educational process and reveal the content of mobile applications in the educational process. The article also touched upon the shortcomings of mobile learning technologies in education. In addition, an overview of the history of mobile learning, an explanation of the term, problems of using mobile technologies in education and the course of its research were presented. Analyzing mobile applications, we present several applications used in training. In the course of the work, the results of a survey conducted to study and analyze the decisive factor for overcoming possible conflicts when using mobile learning in higher education were analyzed.