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Never stop learning : stay relevant, reinvent yourself, and thrive
We now live in a learning economy, says Brad Staats, and while learning has always been important, the returns on lifetime learning are greater than ever. Our primary focus must be on our ability to learn. We must strive to develop new skills to create more value--or be left behind. As Jeff Immelt, Chairman and former CEO of GE, has noted, \"You never hire somebody, no matter what the job you're hiring for, for what they know. You're hiring them for how fast you think they can learn.\" In Never Stop Learning, Staats outlines the framework that will help you become more effective as a lifelong learner. The steps include: Valuing failure Focusing on process, not outcome, and on questions, not answers Making time for reflection Learning to be true to yourself by playing to your strengths Pairing specialization with variety Treating others as learning partners Replete with the most recent research from behavioral science about how we learn as well as engaging stories that show how real learning happens, Never Stop Learning will become the operating manual for your brain in this new environment.-- Provided by publisher
Book
Investigating self-directed learning and technology readiness in blending learning environment
Blended Learning (BL) creates a ‘rich’ educational environment with multiple technology-enabled communication forms in both face-to-face and online teaching. Students’ characteristics are closely related to the learning effectiveness in the BL environment. Students’ ability to direct themselves in learning and to utilise learning technologies can affect student learning effectiveness. This study examined the impacts of self-directed learning, technology readiness, and learning motivation on the three presences (social, teaching, cognitive) among students undertaking subjects in BL and non-BL (NBL) settings. The results indicated that the BL environment provides good facilitation for students’ social involvement in the class. Student technology readiness plays a stronger role in impacting the teaching presence in a BL environment than NBL environment. These findings imply that a proper BL setting creates a cohesive community and enhances collaborations between students. Prior training of learning technologies can potentially enhance students’ teaching presence.
Journal Article
Learning as a generative activity : eight learning strategies that promote understanding
This book presents eight evidence-based strategies that promote generative learning, which enables learners to apply their knowledge to new problems.
Book
An e-Learning Theoretical Framework
E-learning systems have witnessed a usage and research increase in the past decade. This article presents the e-learning concepts ecosystem. It summarizes the various scopes on e-learning studies. Here we propose an e-learning theoretical framework. This theory framework is based upon three principal dimensions: users, technology, and services related to e-learning. This article presents an in-depth literature review on those dimensions. The article first presents the related concepts of computer use in learning across time, revealing the emergence of new trends on e-learning. The theoretical framework is a contribution for guiding e-learning studies. The article classifies the stakeholder groups and their relationship with e-learning systems. The framework shows a typology of e-learning systems' services. This theoretical approach integrates learning strategies, technologies and stakeholders.
Journal Article
An Augmented Reality-based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities
In this study, an augmented reality-based mobile learning system is proposed for conducting inquiry-based learning activities. An experiment has been conducted to examine the effectiveness of the proposed approach in terms of learning achievements and motivations. The subjects were 57 fourth graders from two classes taught by the same teacher in an elementary school in northern Taiwan. The experimental results showed that the proposed approach is able to improve the students' learning achievements. Moreover, it was found that the students who learned with the augmented reality-based mobile learning approach showed significantly higher motivations in the attention, confidence, and relevance dimensions than those who learned with the conventional inquiry-based mobile learning approach.
Journal Article
Emergent learning for wisdom
\"The new millennium presents us with unexpected events that challenge us to think and act in fundamentally different ways. Meeting these challenges requires not only the creation of knowledge but the development of wisdom. This book draws together forty years of scholarship and practice, along with original research, to catalyze our expertise in learning about what we don't know. As evident from the perspective of the learner, a pattern of four distinctive phases of experience - a specific sequence of cognitive, affective, and relationship features - can generate an enhanced perspective out of confusion and lead to wisdom in action\"-- Provided by publisher.
BOOK
Adaptive Learning Using Artificial Intelligence in e‐Learning: A Literature Review
The rapid evolution of e-learning platforms, propelled by advancements in artificial intelligence (AI) and machine learning (ML), presents a transformative potential in education. This dynamic landscape necessitates an exploration of AI/ML integration in adaptive learning systems to enhance educational outcomes. This study aims to map the current utilization of AI/ML in e-learning for adaptive learning, elucidating the benefits and challenges of such integration and assessing its impact on student engagement, retention, and performance. A comprehensive literature review was conducted, focusing on articles published from 2010 onwards, to document the integration of AI/ML in e-learning. The review analyzed 63 articles, employing a systematic approach to evaluate the deployment of adaptive learning algorithms and their educational implications. Findings reveal that AI/ML algorithms are instrumental in personalizing learning experiences. These technologies have been shown to optimize learning paths, enhance engagement, and improve academic performance, with some studies reporting increased test scores. The integration of AI/ML in e-learning platforms significantly contributes to the personalization and effectiveness of the educational process. Despite challenges like data privacy and the complexity of AI/ML systems, the results underscore the potential of adaptive learning to revolutionize education by catering to individual learner needs.
Journal Article
The role of social network analysis as a learning analytics tool in online problem based learning
Background
Social network analysis (SNA) might have an unexplored value in the study of interactions in technology-enhanced learning at large and in online (Problem Based Learning) PBL in particular. Using SNA to study students’ positions in information exchange networks, communicational activities, and interactions, we can broaden our understanding of the process of PBL, evaluate the significance of each participant role and learn how interactions can affect academic performance.
The aim of this study was to study how SNA visual and mathematical analysis can be sued to investigate online PBL, furthermore, to see if students’ position and interaction parameters are associated with better performance.
Methods
This study involved 135 students and 15 teachers in 15 PBL groups in the course of “growth and development” at Qassim University. The course uses blended PBL as the teaching method. All interaction data were extracted from the learning management system, analyzed with SNA visual and mathematical techniques on the individual student and group level, centrality measures were calculated, and participants’ roles were mapped. Correlation among variables was performed using the non-parametric Spearman rank correlation test.
Results
The course had 2620 online interactions, mostly from students to students (89%), students to teacher interactions were 4.9%, and teacher to student interactions were 6.15%. Results have shown that SNA visual analysis can precisely map each PBL group and the level of activity within the group as well as outline the interactions among group participants, identify the isolated and the active students (leaders and facilitators) and evaluate the role of the tutor. Statistical analysis has shown that students’ level of activity (outdegree r
s
(133) = 0.27,
p
= 0.01), interaction with tutors (r
s
(133) = 0.22,
p
= 0.02) are positively correlated with academic performance.
Conclusions
Social network analysis is a practical method that can reliably monitor the interactions in an online PBL environment. Using SNA could reveal important information about the course, the group, and individual students. The insights generated by SNA may be useful in the context of learning analytics to help monitor students’ activity.
Journal Article