Personal Knowledge Management Skills in Web 2.0-Based Learning

Cigognini, Maria Elisabetta; Pettenati, Maria Chiara; Edirisingha, Palitha

doi:10.4018/978-1-60960-783-8.ch505

Cited by 10 publications

(10 citation statements)

References 10 publications

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“…It also assists students and instructors in developing some new technical skills. According to Cigognini et al (2011), well-trained instructors are capable of creating an elearning environment where, through guidance, motivation, and encouragement students can utilize technology as a means of informal learning. This enables, even less motivated students to be more engaged, confident, and selfdependent (Isaeva et al, 2020).…”

Section: Figurementioning

confidence: 99%

“…O'Sullivan et al (2017) argue that, from a social learning theory perspective, socialization --which is exercised in face-to-face learning--is a fundamental element for cognition and understanding. However, this depends on the instructors' skills and guidance on how to implement multi-modality in the educational process, through a combination of technology that is conducive to stimulation and interaction (Cigognini et al, 2011). Concerning the importance of student engagement in online learning, Isayeva (2020) argues that universities…”

Section: Introductionmentioning

confidence: 99%

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Covid-19’s Impact on the Higher Education System in Jordan: Advantages, Challenges, and Suggestions

Haider

Al-Salman

2020

HSSR

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Purpose of the study: The present study surveys the reactions of university-level faculty members in Jordan towards their experience with COVID-19's emergency online learning model. It primarily investigates the advantages of switching to online learning, challenges faced, and suggestions for improving the teaching-learning process. Methodology: The study is based on empirical data compiled from the responses of 432 instructors in six Jordanian public and private universities. The data collection instrument consists of a structured open-ended questionnaire, which comprises three constructs: challenges, advantages, and suggestions for improvement. Similar responses were combined in thematic categories and were calculated to obtain frequencies and percentages. Main Findings: Concerning the advantages, e-learning enabled instructors to use new effective teaching tools and acquire new skills. The challenges were mainly related to technology and the Internet, assessment, interaction, and lack of clear vision and regulations by policymakers. Instructors suggested providing better technical support; blending online with traditional learning; offering more training, and improving the assessment tools and designing new ones. Applications of this study: This study is useful for educational leaders and policymakers providing guidance and insights on how higher education institutions have responded to this global health emergency, and how they managed to meet the evolving needs of students and staff. Consequently, the higher education sector should be prepared to operate more efficiently and effectively for any future emergencies. Novelty/Originality of this study: While different studies have investigated the impact of COVID-19 on the education sector globally, little attention has been given to developing countries in the Middle East. To this end, the present study focuses on how COVID-19 has been effective in reshaping and revolutionizing the higher education paradigm in Jordan through highlighting the advantages, challenges, and subsequent suggestions for improvement.

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Section: Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Covid-19’s Impact on the Higher Education System in Jordan: Advantages, Challenges, and Suggestions

Haider

Al-Salman

2020

HSSR

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“…In light of these revelations, lecturers have to put in more effort in monitoring their students' work, providing guidance (especially for students with difficulties), and instituting pedagogical interventions such that students will be able to learn efficaciously in PLE [2]. Therefore, an effective PLE system that can seamlessly blend both formal and informal learning and monitoring support of student learning is needed.…”

Section: Personalized Learning Environmentmentioning

confidence: 99%

“…According to Kim and Hodges [16], students with low motivation may not learn at all, even though they may have participated in a particular learning activity. Cigognini et al [2] cited that students can become more engaged, motivated, and persistent in partaking in the learning process with closed monitoring and guidance of their instructors whereby the students will feel more confident and secure in using the PLE. Thus, it is important to motivate students to learn in PLE by providing them assistance and guidance by the lecturers.…”

Section: Introductionmentioning

confidence: 99%

Motivating engineering students learning via monitoring in personalized learning environment with tagging system

Balakrishnan

2018

Comp Applic In Engineering

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Personalized Learning Environment (PLE) is a novel pedagogical approach, which has caused a paradigm shift in tertiary education. In this study, a computer‐based PLE system was developed for undergraduate engineering students to help them learn a topic in a Wireless Communications course. The study used a mixed‐method approach, involving interviews and administration of questionnaires, to examine the impact of the system on students’ motivation, and the role of instructors as a motivator. The research instrument used was Science motivation questionnaire (SMQ). The analysis of the data yielded several promising results, notably the students were motivated in learning process using the system and the instructors were satisfied that they could perform the monitoring and motivating tasks effectively. Overall, the findings suggest that such a system has a strong potential to create an effective, appealing PLE to help engineering students engage in learning process with a strong sense of motivation and interest. The study also found out that students exhibited high assessment anxiety and low self‐efficacy in self‐directed learning, thus emphasizing the need to provide them with more guidance and assistance.

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“…In a web based learning environment, students must exercise a high degree of self-regulation to accomplish their learning goals (Dabbagh & Kitsantas, 2004). Cigognini, Pettenati, and Edirisingha (2011) also reported that effective pedagogical measures, including providing learning support and guidance, will help learners make the most of Web 2.0 technologies to achieve their goals.…”

Section: Web 20 E-learning 20 and Self-regulationmentioning

confidence: 99%

Factors Influencing Self-Regulation in E-learning 2.0: Confirmatory Factor Model | Facteurs qui influencent la maîtrise de soi en cyberapprentissage 2.0 : modèle de facteur confirmative

Hong

2016

CJLT / RCAT

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The importance of self-regulation in e-learning has been well noted in research. Relevant studies have shown a consistent positive correlation between learners’ self-regulation and their success rate in e-learning. Increasing attention has been paid to developing learners’ self-regulated abilities in e-learning. For students, what and how to learn are largely predetermined by the learning environment provided by their institutions. Environmental determinants play a key role in shaping self-regulation in the learning process. This paper reports a study on the influences of the e-learning 2.0 environment on self-regulation. The study identified the factors that influence self-regulation in such an environment and determine the relationships between the factors and self-regulation. A theoretical model to categorize the success factors for self-regulated learning was proposed for this kind of environment. Based on the model, a questionnaire was designed and administered to more than two hundred and fifty distance learning students in Beijing and Hong Kong. Through structural equation modeling (SEM) technique, relationships between environmental factors and self-regulation were analyzed. Statistical results showed that several factors affect self-regulation in the e-learning 2.0 environment. They include system quality, information quality, service quality, and user satisfaction. L’importance de la maîtrise de soi en cyberapprentissage a été bien étudiée. Les études pertinentes ont démontré une corrélation positive uniforme entre la maîtrise de soi des apprenants et leurs taux de réussite en apprentissage en ligne. Une attention croissante a été portée au développement des aptitudes de maîtrise de soi des élèves en cyberapprentissage. Pour les élèves, quoi apprendre et comment sont des questions principalement prédéterminées par l’environnement d’apprentissage qu’offrent leurs établissements. Les déterminants environnementaux jouent un rôle clé pour modeler la maîtrise de soi dans le processus d’apprentissage. Cet article rapporte une étude sur les influences de l’environnement de cyberapprentissage 2.0 sur la maîtrise de soi. L’étude a cerné les facteurs qui, dans un tel environnement, influencent la maîtrise de soi et déterminent les relations entre les facteurs et la maîtrise de soi. Un modèle théorique de catégorisation des facteurs de réussite pour l’apprentissage autogéré a été proposé pour ce type d’environnement. Un questionnaire a été conçu selon ce modèle et plus de deux cent cinquante élèves en téléapprentissage à Beijing et à Hong Kong y ont répondu. À l’aide d’une technique de modélisation par équation structurelle, les relations entre les facteurs environnementaux et l’autogestion ont été analysées. Les résultats statistiques ont démontré que plusieurs facteurs affectent l’autogestion dans l’environnement de cyberapprentissage 2.0. Ceux-ci comprennent la qualité du système, la qualité de l’information, la qualité du service et la satisfaction de l’usager.

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Personal Knowledge Management Skills in Web 2.0-Based Learning

Cited by 10 publications

References 10 publications

Covid-19’s Impact on the Higher Education System in Jordan: Advantages, Challenges, and Suggestions

Covid-19’s Impact on the Higher Education System in Jordan: Advantages, Challenges, and Suggestions

Motivating engineering students learning via monitoring in personalized learning environment with tagging system

Factors Influencing Self-Regulation in E-learning 2.0: Confirmatory Factor Model | Facteurs qui influencent la maîtrise de soi en cyberapprentissage 2.0 : modèle de facteur confirmative

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