Mobile learning and student cognition: A systematic review of PK‐12 research using Bloom’s Taxonomy

The use of mobile technology to support teaching and learning in schools, has extended technology learning tools in schools across different socio economic divides. There have been various studies throughout the world which reflect the improvement of such technology in schools. In this chapter we reflect on a series of studies conducted in developing countries with focus on Jantjies and Joy (2012, 2013, 2014, 2015) studies. The studies were conducted in schools with the objective of providing teachers and learners with multilingual mobile learning content specifically designed to support teaching and learning in their science and mathematics classrooms and beyond. This chapter provides a culmination of lessons learnt from all studies reflecting on the journey of mobile learning in schools across South Africa. The use of mobile technology to support teaching and learning in schools, has extended technology learning tools in schools across different socio economic divides. There have been various studies throughout the world which reflect the improvement of such technology in schools. In this chapter we reflect on a series of studies conducted in developing countries. The studies were conducted in schools with the objective of providing teachers and learners with multilingual mobile learning content specifically designed to support teaching and learning in their science and mathematics classrooms and beyond. This chapter provides a culmination of lessons learnt from all studies reflecting on the journey of mobile learning in schools across South Africa.

Investigating the use of innovative mobile pedagogies for school-aged students: A systematic literature review

The use of mobile learning in PK-12 education: A systematic review

Though teacher conceptions of mobile language learning might affect their own language learning and their teaching practices, this is an area seldom examined. To address this paucity of research, fifty-nine students in an MA ELT (English Language Teaching) program, the majority of whom were in-service teachers, were investigated, via an open-ended survey, as to their understanding of mobile language learning and how they undertook mobile language learning and teaching. The results revealed that over eighty percent of the students understood mobile language learning as learning at any time and in any place or as the use of mobile technologies for learning. The participants mainly used mobile devices to practice their listening, reading and vocabulary. A cross-sectional analysis demonstrated that conceptualizing mobile learning as learning at any time and in any place is linked to the practices of listening, reading and online classes, while the conception of mobile learning as using mobile technologies is primarily associated with learning vocabulary, which indicates that conceptions of mobile learning are connected to learning practices. In terms of teaching, the participants reported mobile devices offered the most assistance via enhancing teaching effects, offering richer resources, helping with assigning homework, and communication with parents and students. The findings contribute to our understanding of teacher conceptions of mobile language learning and their teaching practices, which bear significant implications for mobile pedagogy and teacher education.

The currently used resource recommendation algorithm mainly recommends resources according to the user's preference for a tag class, ignoring the relationship between user preferences and needs and learning scenarios under mobile learning, resulting in poor efficiency and accuracy of recommended resources. In order to improve the shortcomings of the algorithm, this paper studies the personalized recommendation algorithm of Ideological and political teaching multimedia resources based on mobile learning. By constructing the map of Ideological and political teaching knowledge, this paper analyzes the correlation between resources. The diagnosis result of students' cognitive level is one of the characteristics of personalized recommendation. Mobile learning devices are used to collect data, calculate and perceive mobile learning scenarios. By improving the collaborative filtering technology, the teaching resources of Ideological and political courses can be personalized recommended. In the algorithm experiment, the average absolute error of the algorithm recommendation is relatively reduced by about 14.67%, the recommendation efficiency is higher, and the personalized recommendation effect is better.

With increasing permeation of mobile devices into people’s everyday life, m-learning can be regarded as the next generation of e-learning. Learning via mobile devices, especially mobile phones, is practiced in educational areas all over the world. This paper describes a mobile language learning project which creates English learning materials and delivers the learning materials to Japanese university students. The data collected from this ongoing mobile language learning project allows us to investigate Japanese students’ mobile learning styles and learning material preferences as well as their concerns about using mobile learning. The data was collected from various sources: online surveys, server logs, user registered personal information, interviews and actual online quiz results. The findings obtained from this research provide useful information for future mobile learning project/system design, implementation and content delivery.KeywordsMobile learning styleslearning preferenceslearning expectationsfindingsfuture mobile learning designJapan

The topic includes four main themes: (1) The Collaborative Work in Cloud Storage Services: The collaborative work is seen as a force for the individual and community. It, in the field of education, expresses the interaction among students of individual differences who work within collaborative aims and skills to achieve a specific aim. In addition, cloud storage predicts a tremendous change in the way information is stored and applications are run. That is, instead of storing information and running programs on PCs, everything will be hosted in a cloud that can be accessed anywhere and processed by addition or deletion collaboratively. (2) Computer- supported collaborative learning environment (CSCL): Collaborative learning is an umbrella term for a variety of educational approaches involving joint intellectual effort by students, or students and teachers together. It is based on the idea that learning is naturally a social act in which the participants talk among themselves. A group of students engaged in collaborative learning works together to achieve shared goals. (3) Mobile learning: Mobile learning is a term that has been used widely in different places all over the world. it has been encouraged to be used in higher education institutions because of a set of factors such as the availability of mobile phones, their ability to motivate students, and the freedom and privacy they provide to share information. Mobile learning is defined as E-learning that uses mobile devices or learning connected to a mobile device, Laouris & Eteokleous. (4) Open-Source Learning Management Systems: The integration of many Educational technologies in education have been widely promoted for their potential to enrich, enhance and extend student-learning experiences. Hence, pioneer educational establishments all over the world try to benefit of these technologies as much as possible to convey knowledge resources to both of the learner and teacher in least time, effort and cost. One of these educational technology tools which has been prominent in the field of education and technology integration is Learning Management Systems known as LMS.

Mobile devices (e.g., smartphones and tablets) are spreading globally, along with decreasing prices and increasing support utilities with the characteristics of availability, flexibility, portability, individuality, connectivity, and social interactivity. The rise of mobile devices/ technologies in school inspired educational researchers to introduce the term “mobile learning” to push the boundaries of traditional pedagogy. This study was a systematic review of 52 articles related to mobile learning in mathematics education in 2008-2021. It answered the questions about distribution, major research purposes, approaches, methods. The articles for review were chosen using a three-stage methodology: read, select criteria, and summarize. This review study of mobile learning presents findings, which highlighted gaps in existing literature on the topic and has provided insights, can become a platform and guidance for researchers, educators, and policy makers for future research.

Learning theories underpin the expectations of meaningful outcomes that any given learning task should have. However, educators' understanding and application of such theories is likely to vary with their own experience and context. In this article, we explore the potential value of a rubric for the design of mobile learning activities that is based on a core set of six learning theories, which we have identified from the literature as being highly relevant to the context of mobile learning. The key concepts of these theories have been used to create the evaluation rubric, which supports the analysis of learning activity design from the perspective of each of the chosen learning theories. The application of this rubric is explored from two perspectives. First, we apply it to an existing mobile learning activity to evaluate to what extent the activity embodies the theories within the rubric. Then we propose a redesigned activity by using the rubric as a guiding framework for improving the task design. This process demonstrates the potential value of applying such a rubric to designing mobile learning activities, to ensure that they adequately leverage the components of one or more relevant theories.

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.

Purpose – This study aims to describe the feasibility of designing and fostering pre-service teacher inquiry at the intersection of community and disciplinary engagement. Mapping My Math (MMM), a game-based and mobile learning activity, guided pre-service teachers in playfully exploring mathematics featured in the everyday activities of people and places and creatively representing this inquiry with digital media. Design/methodology/approach – This study draws from design-based research that examined the role of place, digital media and mobility in mathematics teacher education. Design narrative methods describe how MMM was created, implemented and refined to support disciplinary inquiry across settings given the evolution of tools, activities and practices. The study and design narrative address the following question: How can game-based and mobile learning be designed to support pre-service teachers’ disciplinary inquiry of everyday mathematics? Findings – Findings shared in this study’s design narrative attend to the quality of pre-service teachers’ inquiry-as-play, or expressive mobility situated amonglearners’ social and material relations, disciplinary concepts and the built environment. Research limitations/implications – Implications from this study concern the role of mobile learning in mathematics teacher education to connect school, community and online settings; the potential of gameful design to impact pre-service teacher learning across settings; and the importance of fostering disciplinary inquiry whereby pre-service teachers can “navigate” their own learning. Originality/value – Game-based and mobile learning designs, like MMM, can create the conditions for cross-setting mobility as generative of inquiry-as-play in mathematics teacher education. MMM encouraged pre-service teachers to playfully leverage disciplinary practices that shaped new relationships with mathematics, their city and the mathematics of place and community.

Mobile learning is gaining popularity as it modifies the conventional definition of teaching and learning by using portable devices. In order to cope with identified limitations of mobile learning, while maintaining its transformational potential of using mobile technology in higher education, we proposed a blended mobile learning environment. In this study, we described the mobile blended learning environment and examined its applicability in theatre arts classrooms by presenting and discussing how mobile devices were used in three blended theatre arts classes at a comprehensive university in Macau. Survey and interview data showed that though challenges exist, the fusion of the multichannel teaching approach (m-learning, blended learning, in class/online lectures) has greatly enhanced teaching and learning experiences.

In order to manage the demands of university studies, research suggests that university students should possess efficient self-regulated learning (SRL) skills. The use of mobile learning is believed to enhance SRL skills. Yet, despite the potential benefits of mobile learning, many first-year students encounter challenges in using mobile devices to foster self-regulated learning skills. It is against this backdrop that this study aimed to examine how first-year medical students utilisee mobile learning to foster self-regulated learning. This study employed a Explanatory Sequential Study Design , combining both quantitative and qualitative data. It used the interpretativist and pragmatic paradigms to understand how students perceive and use mobile devices for self-regulated learning. The interpretivist paradigm focused on understanding students’ perspectives, while the pragmatic paradigm aimed to identify effective ways of using mobile devices to promote self-regulated learning. Participants to this study were first-year medical students. The mixed-methods approach aimed to provide a comprehensive understanding of the research problem by collecting data through various methods. Questionnaires gathered quantitative data, while participatory observation, reflective workshops, and focus group discussions provided qualitative data. The theoretical frameworks that guide the study include the Unified Theory of Acceptance and Use of Technology model (UTAUT) (Venkatesh et al., 2003) and Vygotsky's (1978) socio-cultural theory (SCT). The study findings revealed that mobile devices were used by first year medical students to manage and control their learning, both inside and outside the classroom. Notably, significant improvements were observed in cognitive learning strategies, metacognitive self-regulation strategies and resource management learning strategies, including time management. Additionally, the study found that first-year medical students had a positive perception of mobile learning. Furthermore, mobile devices were generally perceived as enablers of self-regulated learning (SRL), providing flexibility, convenience, and access to diverse learning resources. However, distractions and interruptions posed challenges to focus and attention. To mitigate these challenges, strategies such as device management and setting boundaries were suggested. Moreover, first-year medical students expressed the need for support in developing SRL through mobile learning. Guidance in selecting effective mobile applications, opportunities for collaborative learning, and technological skill training were identified as essential forms of support. The study thus recommends integrating mobile learning into curricula to enhance self-regulated learning skills in higher education students, especially among first-year students. Higher education institutions should establish deliberate policies and initiatives for mobile learning programs, especially for first-year students. Educators should offer guidance and training on using mobile learning tools effectively, including information searching skill. However, students should be cautious about distractions from the use of mobile devices.

The use of mobile learning in education is growing at an exponential rate. To best understand how mobile learning is being used, it is crucial to gain a collective understanding of the research that has taken place. This systematic review reveals the trends in mobile learning in science with a comprehensive analysis and synthesis of studies from the year 2000 onward. Major findings include that most of the studies focused on designing systems for mobile learning, followed by a combination of evaluating the effects of mobile learning and investigating the affective domain during mobile learning. The majority of the studies were conducted in the area of life sciences in informal, elementary (5–11 years) settings. Mobile devices were used in this strand of science easily within informal environments with real-world connections. A variety of research methods were employed, providing a rich research perspective. As the use of mobile learning continues to grow, further research regarding the use of mobile technologies in all areas and levels of science learning will help science educators to expand their ability to embrace these technologies.

China’s information technology development is rapid; the organic combination of science and technology and education has promoted the reform of the education system; the education platform supplemented by mobile devices provides students with a new learning mode; student learning is no longer limited by the traditional education system; and learners can use mobile terminals for online learning, self-control learning steps, arrange learning time, and be able to combine their own deficiencies to strengthen learning content. Therefore, this paper discusses the design of English education teaching system in the Internet of Things technology environment, in order to provide students with a good learning environment and improve students’ English integration strength. This paper analyzes the research status of mobile learning at home and abroad, expounds the construction principles of mobile English learning system, and designs and studies the overall structure and functional modules of the system. The application of the system can replace the traditional English learning method and can enable students to improve their English ability through mobile devices. In view of the problems of poor teaching effect and high energy consumption in the traditional Internet of Things education platform, this paper puts forward a teaching effect evaluation method of Internet of Things education platform based on long-term memory network. By analyzing the current situation of the Internet of Things education platform, including its development and structure, this paper constructs the evaluation model of the combination of long-term memory neural network model and gray model and realizes the evaluation of the teaching effect of the Internet of Things education platform. Finally, through the study of the model, the teaching effect of the Internet of Things education platform is evaluated. The experimental results show that when the method is used to evaluate the teaching effect, the operating energy consumption accounts for 84% of the total energy consumption of the system, which proves the effectiveness of the method.