Analysis and assessment of the Jordan National Test for Controlling the Quality of Science Instruction (NTCQSI): a Rasch measurement perspective

The purpose of this study was to analyze and assess the Jordan National Test for Controlling the Quality of Science Instruction (NTCQSI) from the perspective provided by Rasch measurement. The test was administered on a stratified random sample that consisted of 41,556 tenth graders from all over Jordan. The test results were saved in a data bank. A random sample of 150 participants' records was selected from this data bank. To address the purpose of this study, a series of analyses were conducted. WINSTEPS and RUMM programs were used for the analysis. The procedures that were used in this paper might be used by worldwide testing agencies to clarify or outline how Rasch measurement may be used to obtain evidence for the validity of inferences of tests data.     

Exploring How a Study Abroad and International Service-Learning Project Shaped Preservice Teachers’ Understanding of Humanizing Pedagogy

In an attempt to better prepare future teachers to fight against social injustice, support their culturally and linguistically diverse students and wrestle with social and educational complexities around the globe, many education programs have increased the number of study abroad programs and international service learning projects. In this qualitative study, we explored seven preservice teachers’ experiences related to humanizing pedagogy after participating in a study abroad program combined with an international service-learning project in a South African rural community. Analyzing multiple data sources such as interviews and reflective journals, we discovered that the preservice teachers grappled with the political, social, economic, and educational differences they encountered during the international project and wrestled with conflicting ideas and beliefs about poverty and language. They identified their relationships with students as catalysts to address these educational issues and their need to reverse systemic inequities. They built caring relationships with students in the community and developed additive perspectives the focused on the students’ community cultural capital. The preservice teachers expressed deep critical reflection and a desire to promote a more fully human educational world where students have the opportunities to enact their agency, their creativity, and their language and culture.     

Assessing Teacher Opinion on the Inclusion of Children with Social,Emotional and Behavioural Difficulties into Mainstream School Classes

Abstract

This study used a mixed methods approach to determine mainstream teachers’ attitudes towards inclusion of children with social, emotional and behavioural difficulties (SEBD) considering the influence of age, experience, qualifications and the support they receive. The study further considered whether there was a link between attitudes and willingness to work with such children in mainstream classrooms whilst identifying the barriers to successful inclusion. A sample of 50 primary teachers (14 males; 36 females) volunteered to take part in the study. The results indicated that age, time in profession and support received were significant predictors of teacher attitudes, with time in the profession as the strongest predictor. Attitudes also had a significant effect on willingness to include when controlling for support received. Qualitative responses suggested teachers felt they lacked necessary training to include children with emotional and behavioural difficulties, and lack of consistent resources and support were commonly cited as barriers.     

Automating the Construction of Internet Portals with Machine Learning

Domain-specific internet portals are growing in popularity because they gather content from the Web and organize it for easy access, retrieval and search. For example, www.campsearch.com allows complex queries by age, location, cost and specialty over summer camps. This functionality is not possible with general, Web-wide search engines. Unfortunately these portals are difficult and time-consuming to maintain. This paper advocates the use of machine learning techniques to greatly automate the creation and maintenance of domain-specific Internet portals. We describe new research in reinforcement learning, information extraction and text classification that enables efficient spidering, the identification of informative text segments, and the population of topic hierarchies. Using these techniques, we have built a demonstration system: a portal for computer science research papers. It already contains over 50,000 papers and is publicly available at www.cora.justresearch.com. These techniques are widely applicable to portal creation in other domains.     

<Emphasis Type="Italic">EveTAR</Emphasis>: building a large-scale multi-task test collection over Arabic tweets

This article introduces a new language-independent approach for creating a large-scale high-quality test collection of tweets that supports multiple information retrieval (IR) tasks without running a shared-task campaign. The adopted approach (demonstrated over Arabic tweets) designs the collection around significant (i.e., popular) events, which enables the development of topics that represent frequent information needs of Twitter users for which rich content exists. That inherently facilitates the support of multiple tasks that generally revolve around events, namely event detection, ad-hoc search, timeline generation, and real-time summarization. The key highlights of the approach include diversifying the judgment pool via interactive search and multiple manually-crafted queries per topic, collecting high-quality annotations via crowd-workers for relevancy and in-house annotators for novelty, filtering out low-agreement topics and inaccessible tweets, and providing multiple subsets of the collection for better availability. Applying our methodology on Arabic tweets resulted in EveTAR, the first freely-available tweet test collection for multiple IR tasks. EveTAR includes a crawl of 355M Arabic tweets and covers 50 significant events for which about 62K tweets were judged with substantial average inter-annotator agreement (Kappa value of 0.71). We demonstrate the usability of EveTAR by evaluating existing algorithms in the respective tasks. Results indicate that the new collection can support reliable ranking of IR systems that is comparable to similar TREC collections, while providing strong baseline results for future studies over Arabic tweets.     

Recommendations of transgender students,staff, and faculty in the USA for improving college campuses

Research indicates that transgender individuals frequently experience marginalisation and interpersonal victimisation within college and university settings. Missing from the literature is a discussion of what can be done to address such patterns in higher education, based upon empirical data gathered from transgender and gender non-conforming students, staff, and faculty. The present study aimed to fill this gap by reporting on solutions offered by a sample of 30 individuals in one US state while integrating a lens of intersectionality. Five resulting themes include (a) offer education, campus programming, and support for trans individuals; (b) improve university systems and procedures for recording one's name and gender; (c) encourage greater inclusivity and recruitment of diverse groups; (d) make physical changes to facilities; and (e) hold people accountable. These findings suggest institutional actions and policy changes for higher education administrators and others committed to improving campuses for transgender and gender non-conforming people.     

The Effects of a Summary Writing Strategy on the Literacy Skills of Adolescents with Disabilities

Many adolescents, particularly adolescents with disabilities, have difficulty with literacy tasks such as reading and writing. Yet research has found that when students with disabilities receive appropriate instruction, they typically are able to improve their overall writing outcomes. This study explored the effectiveness of a summary writing strategy taught through a mnemonic device (WINDOW) with prompts for self-regulation on the summary writing and reading comprehension of high school students with disabilities. Results indicated that the students who received the intervention wrote longer and higher quality summaries and improved their reading comprehension scores after learning the strategy when compared to a control group. These outcomes indicate that the WINDOW strategy may have the potential to improve reading and writing outcomes for high school students with disabilities. Implications for practice and future research are discussed.