2,632 research outputs found

    Application of a virtual scientific experiment model in different educational contexts

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    E-learning practice is continuously using experimentation in order to enhance the basic information transfer model where knowledge is passed from the system/ tutors to the students. Boosting student productivity through on-line experimentation is not simple since many organizational, educational and technological issues need to be dealt with. This work describes the application of a Learning Model for Virtual Scientific Experiments (VSEs) in two different scenarios: Information and Communication Technologies and Physics. As part of the first, a VSE for Wireless Sensor Networks was specified and deployed while the second involved the specification and design of a collaborative VSE for physics experiments. Preliminary implementation and deployment results are also discussed

    Investigating factors affecting students’ performance to PISA Science items

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    The present paper aims to investigate, on the one hand, the extent to which PISA Science items validly assess the knowledge and skills of 15 year-old Greek students, while, on the other hand, to examine the effect of the following factors: student’s gender, scientific processes and contexts (situations) on the students’ performance in these PISA items. The research used paper-and-pencil test with published PISA Science items, conducted individual semi-structured interviews with 15 year-old students and finally marked the students’ responses, according to the PISA marking guide. Τhe basic finding resulting from the data analysis is that the paper-and-pencil test with the PISA Science items does not tend, unlike the interview, to effectively record the Greek students’ Science knowledge and skills. Moreover, the analysis revealed that the performance of students in the PISA Science items (paper-and-pencil test and interview) tend to be independent of the student’s gender and depend on the context in which the knowledge and processes are assessed. Additionally, the possible correlation between the students’ performance and the factor of scientific processes seems to depend on the setting in which the students provide their responses (paper-and-pencil test or interview)

    Predicting Students’ Performance by Learning Analytics

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    The field of Learning Analytics (LA) has many applications in today’s technology and online driven education. Learning Analytics is a multidisciplinary topic for learn- ing purposes that uses machine learning, statistic, and visualization techniques [1]. We can harness academic performance data of various components in a course, along with the data background of each student (learner), and other features that might affect his/her academic performance. This collected data then can be fed to a sys- tem with the task to predict the final academic performance of the student, e.g., the final grade. Moreover, it allows students to monitor and self-assess their progress throughout their studies and periodically perform a self-evaluation. From the edu- cators’ perspective, predicting student grades can help them be proactive, in guiding students towards areas that need improvement. Moreover, this study also takes into consideration social factors that might affect students’ performance

    Sentiment Analysis of Teachers Using Social Information in Educational Platform Environments

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    © 2020 World Scientific Publishing Company. Electronic version of an article published as International Journal on Artificial Intelligence Tools, Vol. 29, No. 02, 2040004 (2020): https://doi.org/10.1142/S0218213020400047.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.Peer reviewe

    Ariel - Volume 5 Number 1

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    Editors Mark Dembert J.D. Kanofskv Entertainment Editor Robert Breckenridge Gary Kaskey Editor Emeritus David A. Jacoby Photographer Scott Kastner Staff Richard Blutstein Bob Johnson John R. Cohn Joseph Sassani Ken Jaffe Bob Sklarof

    Undereducation, Motivating Intervention in Rural Schools with MAPPS

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    Many primary school students in rural areas of developing countries perform poorly in national final exams, and therefore, fail to transit to secondary schools. This problem causes undereducation and shortage of skilled manpower in the developing countries. Mobile Academic Performance Prediction System (MAPPS) is a technology that categorises students into two groups: those requiring high intervention and those requiring low intervention. This study investigates predicting the students that need high intervention in order to motivate initiation of intervention measures early enough. The focus in this paper is the mobile application design process and the usability evaluation of MAPPS

    Independent Validation and Clinical Utility Study of the Hellenic WISC-III Using a Greek-Cypriot Sample

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    The Hellenic WISC-III (Wechsler, 1997) is currently the only standardized and officially published tool for the assessment of the intelligence of children and adolescents in Greece. The test is also used with caution in Cyprus, among Greek speakers, but no specific norms exist for use in this country. The purpose of this study was to provide evidence of the qualities of the test using an independent Greek-Cypriot sample and to support its utility in the psychological evaluation of Greek speaking children in Cyprus. The participants were 151 public school children aged 9:1 to 15:8 years. Correlations between the subtests of the WISC-III and the Scale IQs and, also, correlations between scores on the WISC-III and achievement measures as well as the educational level of parents provided evidence of convergent - construct validity. Low correlations between scores on the WISC-III and measures of psychopathology supported the instruments divergent - construct validity. Also, an exploratory factor analysis further supported the construct validity of the test. Moreover, the study provided evidence in support of the predictive validity and clinical utility of the test by examining the cognitive profiles on the Hellenic WISC-III of children with learning difficulties and identifying the WISC-III subscale scores that best distinguish them. This evidence is very important for clinicians in Cyprus but, also, further supports the international evidence about the utility of the Wechsler ability scales

    An empirical evaluation of e-learning usage in the higher education context

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    [EN] E-learning has been adopted for several years in Greece and abroad, and it is considered an integral part of blended learning. E-learning systems accumulate a vast amount of data which may be very valuable. The educational organizations may exploit the power provided by e-learning, if they analyze the usage and the content of the courses. An early assessment of the of e-courses use may provide useful information to the educators, in order to make educational interventions in their teaching material. This study suggests that the evaluation of e-learning usage may be carried out with the assesment of variables and metrics related to teacher training material and student trafficking. We propose three metrics which are combined efficiently, in order to quantify the quality characteristics of the courses and offer useful insights about the educational material and e-learning usage. This case study was implemented in the e-class platform of a Greek Higher Education educational institute. This platform created by the Greek Universities Network (GUNET) is very popular in Greece, since the majority of the Greek universities have adopted it. The results of our study confirmed the validity of our suggested approach, and highlighted the need for a more learnercentered focus and active participation of the students.Petasakis, I.; Kontogiannis, S.; Gounopoulos, E.; Kazanidis, I.; Valsamidis, S. (2020). An empirical evaluation of e-learning usage in the higher education context. Editorial Universitat Politècnica de València. 291-300. https://doi.org/10.4995/INN2019.2019.10147OCS29130

    Health Behaviors Among College Students: The Influence of Future Time Perspective and Basic Psychological Need Satisfaction

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    Health behavior change may prevent many fatal diseases, and may be influenced by social and motivational constructs. We assessed the interaction effect of future time perspective and basic psychological need fulfillment on positive and negative health behaviors. Future time perspective was associated with more positive, and less negative, health behaviors. Need fulfillment was associated with only positive health behaviors. In moderation analyses, individuals reporting both high need fulfillment and future perspective reported greater positive health behaviors, and were especially unlikely to smoke. Enhancing future-mindedness and supporting need satisfaction in interventions targeting modifiable health behaviors is encouraged
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