Urban High School Students’ IT/STEM Learning: Findings from a Collaborative Inquiry- and Design-Based Afterschool Program

This exploratory study examines the impact of a collaborative inquiry- and design-based afterschool program on urban high school students’ IT/STEM learning—using information technology (IT) within the context of science, technology, engineering, and mathematics (STEM). The study used a mixed methods design, involving 77 participants within two cohort groups, each participating in an eighteen-month intervention period. Data were collected from the pre- and post-surveys, analysis of the participants’ IT/STEM projects, external evaluation reports, and follow-up interviews. Findings indicate that the program had a significant impact on students’ technology and IT/STEM skills, frequency of technology use, and understanding of IT use in STEM-oriented fields. Some degree of impact on attitude changes toward IT/STEM and career aspirations in these fields was also in evidence. The study demonstrates that IT/STEM experiences supported through technology-enhanced, inquiry- and design-based collaborative learning strategies have significant impact on urban high school students’ IT/STEM learning. Effect of afterschool programs on attitude changes and IT/STEM-related career aspirations of urban high school students are recommended areas of further investigation.     

Intelligent topic selection for low-cost information retrieval evaluation: A New perspective on deep vs. shallow judging

While test collections provide the cornerstone for Cranfield-based evaluation of information retrieval (IR) systems, it has become practically infeasible to rely on traditional pooling techniques to construct test collections at the scale of today’s massive document collections (e.g., ClueWeb12’s 700M+ Webpages). This has motivated a flurry of studies proposing more cost-effective yet reliable IR evaluation methods. In this paper, we propose a new intelligent topic selection method which reduces the number of search topics (and thereby costly human relevance judgments) needed for reliable IR evaluation. To rigorously assess our method, we integrate previously disparate lines of research on intelligent topic selection and deep vs. shallow judging (i.e., whether it is more cost-effective to collect many relevance judgments for a few topics or a few judgments for many topics). While prior work on intelligent topic selection has never been evaluated against shallow judging baselines, prior work on deep vs. shallow judging has largely argued for shallowed judging, but assuming random topic selection. We argue that for evaluating any topic selection method, ultimately one must ask whether it is actually useful to select topics, or should one simply perform shallow judging over many topics? In seeking a rigorous answer to this over-arching question, we conduct a comprehensive investigation over a set of relevant factors never previously studied together: 1) method of topic selection; 2) the effect of topic familiarity on human judging speed; and 3) how different topic generation processes (requiring varying human effort) impact (i) budget utilization and (ii) the resultant quality of judgments. Experiments on NIST TREC Robust 2003 and Robust 2004 test collections show that not only can we reliably evaluate IR systems with fewer topics, but also that: 1) when topics are intelligently selected, deep judging is often more cost-effective than shallow judging in evaluation reliability; and 2) topic familiarity and topic generation costs greatly impact the evaluation cost vs. reliability trade-off. Our findings challenge conventional wisdom in showing that deep judging is often preferable to shallow judging when topics are selected intelligently.     

Towards automated software model checking using graph transformation systems and Bogor

Graph transformation systems have become a general formal modeling language to describe many models in software development process. Behavioral modeling of dynamic systems and model-to-model transformations are only a few examples in which graphs have been used to software development. But even the perfect graph transformation system must be equipped with automated analysis capabilities to let users understand whether such a formal specification fulfills their requirements. In this paper, we present a new solution to verify graph transformation systems using the Bogor model checker. The attributed graph grammars （AGG）-like graph transformation systems are translated to Bandera intermediate representation （BIR）, the input language of Bogor, and Bogor verifies the model against some interesting properties defined by combining linear temporal logic （LTL） and special-purpose graph rules. Experimental results are encouraging, showing that in most cases our solution improves existing approaches in terms of both performance and expressiveness.     

A new pedagogical design for geo-informatics courses using an e-training support system

The current study seeks to introduce a new pedagogical design for geo-informatics courses using an e-training support system. Laurillard’s conversational approach based on conceptual representation for both instructor and learner was used to form the framework. As the current study specifically interested in training as a special form for learning, so, we sought methods and strategies to integrate requirements of both company and employee into the design of training programs. Therefore, a competency perspective was adopted into the conversational framework to use learning design that leads to learning activities tightly related to the needs of the company and employee. The above framework has been developed with special consideration to the underpinning pedagogical principles and the needs of lifelong learning that continues after the training has been completed. The implementation of the developed framework needs a special computerized system, so an e-training support system (ETSS) was developed to realize the framework. ETSS is an open source and standard-based infrastructure to enable and foster competence development and exchange of learning activities and learning units. Although the domain of the current study focuses on geo-informatics, ETSS is applicable to any other domain. The developed framework through its ETSS implementation were evaluated in a typical training environment. The results indicated that the best method in training was the training with the developed system with 91.5 % in comparison with the traditional training method with 81.4 %.     

An organic view of students’ want formation: pragmatic rationality,habitus and reflexivity

Based on interviews with and questionnaires completed by upper secondary school pupils (n = 27) from academic and vocational programmes, respectively, the present paper focuses on some of the social and individual conditions that precede the individual decision-making process in education transitions. The paper shows that an organic view of decision-making is in better accordance with observations than is a hierarchical view, and thus supports previous research claiming that pragmatic rationality (based on habitus and reflexivity) plays a more important role in students’ decision-making processes than does instrumental rationally.     

French immersion in Canada: Theory and practice

French immersion programs are rapidly becoming an integral part of the Canadian education system. Its educational and linguistic achievements have been the subject of an abundant literature that continues to grow. The popularity of the program has helped it expand at a phenomenal rate. From one school and a handful of students in the experimental classes 25 years ago, there are now more than 17,000 schools offering French immersion instruction to close to 250,000 students in all major Canadian cities.The major theoretical foundations on which French immersion was explicitly and sometimes implicitly based may be summarized as follows:

Authenticity in teaching and teachers’ emotions: a hermeneutic phenomenological study of the classroom reality

This study probed the conceptualization of authenticity in teaching and its link to teachers’ emotional life through critical emotional praxis because emotions are integral to discovering who we really are (McCarthy, E. D. 2009. “Emotional Performances as Dramas of Authenticity.” In Authenticity in Culture, Self, and Society, edited by P. Vannini, and J. P. Williams, 241–255. London: Ashgate). The participants were 20 Iranian university teachers. Data were collected using interviews, field notes, and observation and were analyzed through the lens of hermeneutic phenomenology. The results revealed that authenticity in teaching consisted of themes of being one’s own self, horizon of significance, and contestation resulted from the sense of responsibility, authentic relations, and de-constructive thinking which confirmed the dialogical nature of authenticity. The emotions connected to authenticity in teaching were Transition-Anger, love, and caring indicating that authenticity in teaching was a practice toward socially just teaching.     

Towards a personality understanding of information technology students and their IT learning in UAE university

This research investigates the personality characteristics of Information Technology students (CIT) in UAE University (UAEU) and how such features impact their IT learning. To achieve this objective, this research attempts to explain the impact of the Big-5 factors on learning using survey research. Results from 179 respondents suggested that agreeableness, extraversion, openness, and conscientiousness respectively were the most important strategies adopted by CIT students. However, neuroticism scored the lowest. Such results could be attributed to personal as well as to cultural reasons as highlighted in this research. The research highlights theoretical as well as professional contributions and implications. Some of challenges in this research could be addressed by designing programs aiming at enhancing student’s learning ability from the perspective of their personal traits.     

The Potentials of Using Mobile Technology in Teaching Individuals with Learning Disabilities: A Review of Special Education Technology Literature

Within the literature, a respectful number of studies related to the use of assistive technologies for special education, resulting in an enormous agenda that encompasses various types of assistive technology applied across disabilities in different types of curricula. These disabilities include, but are not limited to: learning disabilities, mild, moderate and severe mental retardation, speech and communication disorders, hearing and speaking disabilities, and autism Hence, under the intertwined and overlapping umbrellas of assistive technologies and special education, mobile technology finds its promising, new spot on the surface of emerging assistive technologies in the field of special education. This paper addresses the potentials of using mobile technology in teaching individuals with developmental disorders based on current literature.