Research suggests students' use of information and communication technology (ICT) may be more a matter of digital literacy and access rather than a generational trait. We sought to identify ICT preferences of post-secondary students (N = 580) through a Digital Propensity Index (DPI), investigating communication methods, Internet practices and the creation of online content. Age, gender and socioeconomic status were examined as factors which might explain why students use ICT. Results suggest age is a factor in ICT use but that it is not the most important consideration; the gender gap and gaps between socioeconomic groups in terms of ICT use may be closing. The findings raise a variety of implications for institutions training pre-service teachers, curriculum developers designing instructional materials and educational leaders developing ICT policy for schools.

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This systematic review explored methods of UDL implementation for postsecondary students with and without disabilities and the degree to which these methods are effective. The authors examined 17 empirically based studies published across 12 journals focused on the application of UDL principles. The studies were analyzed with regard to 1) participant information, 2) courses and delivery mode, 3) independent and dependent variables, 4) implementation strategies, and 5) effectiveness of implementation. The analysis revealed that 15 of the studies reported effective outcomes, one study resulted in blended effects, and one did not discuss implementation. Two studies used a blended delivery mode for special education courses, and four studies used online delivery modes for a teacher education course and three professional development programs. Other studies used face-to-face instruction for teacher education, general courses, and workshops. The most common independent variables were UDL principle-based course design and implementation, followed by hands-on activities, training of instructors, peer-led team learning, and a collaborative professional development model. The dependent variables included course evaluation, learning outcomes, such as revision of lesson plans and technology use, and level of confidence or acquisition of knowledge about UDL and disabilities. Finally, multiple instructional strategies focusing on the UDL principles were utilized, to include web-based computer-mediated communication, web-based class management systems, interactions with technol

A study (N ¼ 1,995) is presented that investigated whether the Big Five Inventory personality types-agreeableness, conscientiousness, extroversion, neuroticism, and openness-can be used in explaining mobile game play. The study is predicated on research suggesting that relationships exist between certain personality types and willingness to embrace technology and mobile phone ownership. The same might be argued between personality and certain mobile apps, to include games. Little research, however, has examined personality and mobile games. This is unfortunate, as these games lend themselves naturally to problem-solving challenges and are believed to aid with learning. Findings revealed that agreeableness was the most significant personality type in predicting frequency and number of hours spent playing mobile games, while openness was the most consistent predictor of mobile gaming as a whole. However, overall strength of associations was weak, suggesting care in using personality, as it may be a poor predictor.

The purposes of this study were to identify the factors that underlie assistive technology (AT) and to validate items to be used in an instrument to evaluate AT use. The study consisted of four phases. First, 99 items were developed though a comprehensive literature review. Second, the items were refined through three layers of review. Third, 1,467 respondents rated the results of the reviews. Fourth, exploratory factor analysis, and three confirmatory factor analyses (CFA) were employed to analyze the data. The results of the CFA were statistically significant (root mean square error of approximation [RMSEA] = 0.036, p = 0.00) with a total of 67 items across 8 factors (effectiveness, affordability and dependability, utility, external support, operations, longevity, discomfort, and compatibility).