“Individual Differences in Self-regulated Learning and Students’ Achievement in Online Courses”
by: Dina M. Schwam
Self-regulated learning, a complex construct, involves three phases that a successful learner works through, referred to as forethought, performance, and self-reflection. Research has demonstrated that self-regulated learning is related to academic achievement, and that academic achievement and self-regulated learning can be improved with explicit instruction. Researchers have found that students enter college courses with varying levels of self-regulated learning skills and that online courses require a higher degree of self-regulated learning skills than other courses. In previous research, five self-regulating learning profiles have been identified in non-traditional students enrolled in online degree programs. These profiles run a spectrum from no self-regulated learning skills to superior self-regulated learning skills. With more courses being offered online at traditional universities, it is important to understand the self-regulated learning profiles of traditional students attending on line classes. It is also important to understand what factors may contribute to self-regulated learning such as age, education level, prior online experience, and comfort level in an online format. This information will inform universities of specific learning programs that may be needed. In this study I will focus on investigating if the five self-regulating learning profiles found by other researchers can be replicated in students attending online classes in a traditional university as well as the effects of self-regulated learning profiles on academic achievement. In addition, in the current study I will also explore how age, education level, prior online experience, and comfort level in taking online courses contribute to self-regulated learning profiles.
“A Systemic Analysis of Presence in Asynchronous Online Undergraduate Courses Using Structural Equation Modeling”
by: Johnathan Yerby
This study seeks to explore the effects of teaching, social, and cognitive presence on interaction and student course satisfaction in an asynchronous online course. Data will be collected using elements of an existing validated survey based on the community of inquiry (Col) model (Arbaugh et al., 2008; D. R. Garrison, Anderson, & Archer, 2000), The Noel-Levitz Priorities Survey for Online Learners (Ruffalo Noel Levitz, 2016), and the Distance Education Learning Environments Survey (S. L. Walker & B. J. Fraser, 2005). Results will be estimated using confirmatory factor analysis and structural equation modeling (Shea & Bidjerano, 2009). This study is meant to add to the literature on asynchronous online learning, but also serve as a model for future research and development.
“Parents’ and Children’s Oral Language Use during Three Gaming Contexts”
by: Dariush Bakhtiari
The oral vocabulary knowledge that young children acquire prior to school entry is foundational to their ability to learn to read (Whitehurst & Lonigan, 1998). Parents are typically children’s first teachers, and research has shown that children’s oral vocabulary knowledge is linked to parent-child interactions (Hart & Risley, 1995; Rowe, 2012; Senechal, LeFever, Thomas, & Daley, 1998; Tamis-LeMonda, Bornstein, Baumwll, 2001; Taylor, 2011). Additionally, parent communication with their children has been seen to differ depending upon the context (Crain-Thorson, Dahlin, & Powell, 2002; Kaefer, Neuman, & Pinkham, 2015; Sosa, 2015). In this study, parents and their 3 and 4 year old children will be audiotaped while they play together in 3 different gaming contexts: a board game, a digital/video game, and while playing with toys. Specifically, this study addresses three research questions: 1) Are there differences in oral vocabulary used by parents and their children in three different gaming contexts: free play with toys, a board game, and a digital game?; 2) What is the nature of the relationship between parents’ and children’s oral vocabulary knowledge and use during game play and on standardized vocabulary assessments?; and 3) After accounting for children’s age and parents’ education levels, what characteristics of parents’ oral vocabulary knowledge and use explain significant variance in children’s oral vocabulary knowledge and use? Each parent and child will have their expressive and receptive vocabulary knowledge measured using the Expressive Vocabulary Test- Second Edition (Williams, 2007) and the Peabody Picture Vocabulary Test- Fourth Edition (Dunn & Dunn, 2007). The parents’ and children’s verbal exchanges during the three different gaming contexts will be audiotaped, and their total number of words spoken, total number of different words spoken, mean length of utterance, number of rare words, and type-token ratio will be calculated. To answer the research questions, descriptive analyses (i.e., mean, standard deviations, range, and totals), multiple analyses of variance, correlations, and multiple linear regression analyses will be conducted.