A highly motivated blended learning model oriented to computer engineering educators

Angelopoulos, Panagiotis; Paraskevas, Michael; Perikos, Isidoros; Zarouchas, Thomas

doi:10.1109/iccse.2014.6926503

Cited by 8 publications

(5 citation statements)

References 3 publications

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“…The challenge of blended learning is the effective integration of face-to-face (F2F) seminars instruction and the complementary application of online-technologies [1,5]. To accomplish this challenge, usually the following procedures are usually integrated: (a) synchronous instant messaging, (b) web based video conferencing, (c) course management software systems, (d) reference online material and (e) electronic surveys.…”

Section: Blended Learning Coursementioning

confidence: 99%

“…This was an optimal approach, since GSN delivers high quality and a wide range of network and telematics services to its end users [4] that exhibit high level of availability and scalability and its modular architecture enables the integration of the Hybrid Education Platform (HEP) described below [1].…”

Section: Introductionmentioning

confidence: 99%

“…On-going and near future actions in both primary and secondary education, evolve the adoption of innovative digital technologies, that entirely transform traditional and lecturedominant teaching methods and potential reform flexible and attractive digital learning environments. In order these actions achieve their potential goals targeted training courses are provided to computer engineering and science educators, following closely the design principles of an appropriate structured blended learning model proposed by the Greek School Network (GSN) and Networking Technologies Directorate (http://nts.cti.gr) [1,2,3]. Formally, the proposed training course efficient combines synchronous e-learning activities and collaborative face-to-face (F2F) training seminars.…”

Section: Introductionmentioning

confidence: 99%

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A Methodology for Evaluation and Knowledge Extraction from On-going Learning Process

Perikos

Angelopoulos

Paraskevas

et al. 2014

2014 IEEE 17th International Conference on Computational Science and Engineering

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This study presents the utilization of a Hybrid Education Platform for the realization of a versatile blended learning model oriented to computer engineering and science educators. Furthermore, a data mining approach is introduced to analyze the questionnaires that learners submit concerning the learning activities they have participated in. Specifically, a clustering and classification methodology framework is followed in order to efficiently examine and extract behavioral trends of the participants. Preliminary results indicate the robustness of the proposed methodology scheme which can potential be applied to various evaluation tasks.

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Section: Blended Learning Coursementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Methodology for Evaluation and Knowledge Extraction from On-going Learning Process

Perikos

Angelopoulos

Paraskevas

et al. 2014

2014 IEEE 17th International Conference on Computational Science and Engineering

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“…The data used in our work, are set of reviews of teachers that participated in lifelong learning courses which were conducted by the Greek School Network. More specifically, the reviews were made by over 2600 of teachers who participated in e-Learning courses on computer science [46][28] [47] which were offered through teleconference services [19] and the teachers expressed their opinions and experiences by answering multiple choice and open-ended questions [8] [45]. After the collection of the teachers' opinions and their textual data, their comments were analyzed by experts and they were manually annotated.…”

Section: Description Of the Textual Datamentioning

confidence: 99%

Sentiment Analysis of Teachers Using Social Information in Educational Platform Environments

Spatiotis

Perikos

Mporas

et al. 2020

Int. J. Artif. Intell. Tools

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Learners’ opinions constitute an important source of information that can be useful to teachers and educational instructors in order to improve learning procedures and training activities. By analyzing learners’ actions and extracting data related to their learning behavior, educators can specify proper learning approaches to stimulate learners’ interest and contribute to constructive monitoring of learning progress during the course or to improve future courses. Learners-generated content and their feedback and comments can provide indicative information about the educational procedures that they attended and the training activities that they participated in. Educational systems must possess mechanisms to analyze learners’ comments and automatically specify their opinions and attitude towards the courses and the learning activities that are offered to them. This paper describes a Greek language sentiment analysis system that analyzes texts written in Greek language and generates feature vectors which together with classification algorithms give us the opportunity to classify Greek texts based on the personal opinion and the degree of satisfaction expressed. The sentiment analysis module has been integrated into the hybrid educational systems of the Greek school network that offers life-long learning courses. The module offers a wide range of possibilities to lecturers, policymakers and educational institutes that participate in the training procedure and offers life-long learning courses, to understand how their learners perceive learning activities and specify what aspects of the learning activities they liked and disliked. The experimental study show quite interesting results regarding the performance of the sentiment analysis methodology and the specification of users’ opinions and satisfaction. The feature analysis demonstrates interesting findings regarding the characteristics that provide indicative information for opinion analysis and embeddings combined with deep learning approaches yield satisfactory results.

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“…Such a system can be used for pure elearning, but is more usually used for a hybrid format, blending traditional face-to-face learning and online asynchronous learning. In addition e-learning can use web-conferencing software, such as Adobe Connect for real-time, so called "synchronous" communication [3] [4].…”

Section: Introductionmentioning

confidence: 99%

Time-shifted learning: Merging synchronous and asynchronous techniques for e-learning

Worthington

2015

2015 10th International Conference on Computer Science &Amp; Education (ICCSE)

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E-learning techniques are usually classified into two broad categories: synchronous and asynchronous. The core question of this research is how to combine synchronous and asynchronous techniques in e-learning software, so it can have a stronger connection with constructivist education. The benefits and drawbacks of existing e-learning software is looked at broadly. Three popular elearning packages used at the Australian National University are investigated: Adobe Connect (synchronous), Moodle and edX (asynchronous). The results of a brief survey of edX students is reported. Using the results of this work a team of students at the ANU Research School of Computer Science is now implementing enhanced asynchronous software to be plugged into Moodle and other asynchronous e-learning packages.

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A highly motivated blended learning model oriented to computer engineering educators

Cited by 8 publications

References 3 publications

A Methodology for Evaluation and Knowledge Extraction from On-going Learning Process

A Methodology for Evaluation and Knowledge Extraction from On-going Learning Process

Sentiment Analysis of Teachers Using Social Information in Educational Platform Environments

Time-shifted learning: Merging synchronous and asynchronous techniques for e-learning

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