Measuring the Impact of ICTs on Academic Performance: Evidence From Higher Education in Tunisia     

Chiraz Karamti 《Journal of Research on Technology in Education》2016,48(4):322-337

Measuring the impact of information and communication technologies (ICTs) is a contemporary question of interest. Despite the general acceptance that ICTs are changing ways of learning, empirical research conducted to date does not consistently verify the efficacy of such changes. Several studies supporting positive impacts of ICTs on achievement relate mainly to developed countries. Focusing on tertiary education in Tunisia, this article attempts to highlight the gap in knowledge about the effects of ICT on education in developing countries by providing evidence from this region. Using survey data involving 377 college students and teachers, a multilevel analysis was conducted to measure the impact of ICT access and use with other student, university, and teacher attributes that may affect academic performance. The results provided evidence for a distinctive, though negative, effect of ICT on performance. These findings raise questions about the effectiveness of educational policies in Tunisia. The findings suggest also that overall university support is essential in increasing ICT learning impacts.  相似文献   

Hybrid query expansion model for text and microblog information retrieval     

Meriem Amina Zingla  Chiraz Latiri  Philippe Mulhem  Catherine Berrut  Yahya Slimani 《Information Retrieval》2018,21(4):337-367

Query expansion (QE) is an important process in information retrieval applications that improves the user query and helps in retrieving relevant results. In this paper, we introduce a hybrid query expansion model (HQE) that investigates how external resources can be combined to association rules mining and used to enhance expansion terms generation and selection. The HQE model can be processed in different configurations, starting from methods based on association rules and combining it with external knowledge. The HQE model handles the two main phases of a QE process, namely: the candidate terms generation phase and the selection phase. We propose for the first phase, statistical, semantic and conceptual methods to generate new related terms for a given query. For the second phase, we introduce a similarity measure, ESAC, based on the Explicit Semantic Analysis that computes the relatedness between a query and the set of candidate terms. The performance of the proposed HQE model is evaluated within two experimental validations. The first one addresses the tweet search task proposed by TREC Microblog Track 2011 and an ad-hoc IR task related to the hard topics of the TREC Robust 2004. The second experimental validation concerns the tweet contextualization task organized by INEX 2014. Global results highlighted the effectiveness of our HQE model and of association rules mining for QE combined with external resources.  相似文献