The increase in college classes being taught online raises concerns about whether all students are well-prepared to learn remotely. In the context of online learning, readiness refers to preparedness for instruction delivered other than face to face (F2F), confidence in using electronic communication, and the ability to engage in autonomous learning (Dada, 2006; Warner, Christie, & Choy, 1998; Xiong, So, & Toh, 2015). Students who are under-prepared may face an uphill battle of trying to learn course content while simultaneously figuring out how to use technology effectively. They may struggle with understanding how to use the course-management system and how to contact the instructor and classmates (Fair & Wickersham, 2012). Consequently, course-completion and program-retention rates tend to be lower in distance-education courses than they are F2F (Ali & Leeds, 2009; Angelina, Williams, & Natvig, 2007; Carr, 2000; Holder, 2007; Lee & Choi, 2011; Mayes et al., 2011). What’s more, such adverse effects may have an inequitable impact on underrepresented students (Lederman, 2020; Xu & Jaggers, 2014). Thus, promoting readiness is essential for enhancing student success (Vonderwell, 2004).
One aspect of readiness is knowing where to turn for help to resolve technology issues and to keep up with coursework (Fair & Wickersham, 2012). Students often report lack of support from the institution as one reason for course withdrawal (Erdil, 2007; Yukselturk & Inan, 2006). Some students may not have access to the Internet or may be in need of a laptop, whereas others may have children at home (Watkins, Leigh, & Triner, 2004) or may struggle with loneliness and social isolation (Cho, Shen, & Laffey, 2010; McInnerney & Roberts, 2004).
A number of factors affect the degree of student readiness for remote learning. Some students are more adept at self-directed learning, which requires taking initiative, with or without the help of others, in determining one’s own learning needs and goals, accessing resources, implementing learning strategies, and evaluating learning outcomes (Knowles, 1975). Others are more motivated to learn remotely, especially as it pertains to collaborative online learning (Xiong et al., 2015). Motivation for learning is associated with lower drop-out rate, more effective learning strategies, and greater course satisfaction (Czubaj, 2004). Learner control, the degree to which a student can direct their own learning experience (Shyu & Brown, 1992), is another characteristic that affects readiness. Students who are more prepared to regulate their own learning may do better in an asynchronous environment. Another consideration is online communication self-efficacy, which involves beliefs about one’s abilities to create opportunities for online interaction with students and the instructor (Hung, Chou, Chen, & Own, 2010; McVay, 2001). Some students are more adept than others at asking questions and reaching out to classmates in a virtual environment. A closely related construct is social competencies with classmates, which are the “skills, competencies, and the feeling of control essential for managing social situations and building and maintaining relationships” (Myllylä & Torp, 2010). Several authors support the importance of social competencies for success in distance learning (Chen, Huang, Chang, Wang, & Li, 2010; Parker, Hogan, Eastabrook, Oke, & Wood, 2006; Williams, 2003). In addition, self-efficacy about technical competencies, which pertain to students’ beliefs about their abilities to use technology for e-learning (Cigdem & Ozturk, 2016), can affect readiness. Such competencies may be associated with both computer skills and Internet-searching capabilities. Finally, lifestyle is another issue to consider. For some students, issues in life (e.g., at work or at home) may either impede or aid online learning, depending upon the circumstances (Watkins, et al., 2004).
In light of these factors, it is not surprising that student readiness for remote learning is positively correlated with achievement in online courses (Artino, 2008; Lee, Shen, & Tsai, 2008; Liaw & Huang, 2013; Paechter, Maier & Macher, 2010; Puzziferro, 2008; Wang, Shannon & Ross, 2013; Yukselturk & Bulut, 2007). Consequently, the Remote Learner Readiness Assessment (RLRA) was developed as an additional subscale for the Student Strengths Inventory (SSI). The RLRA enables students to self-assess self-directed learning, learner control, online communication self-efficacy, social competencies with classmates, technical competencies, and lifestyle issues. Items related to motivation were not included because the SSI already contains items connected to that construct.
The RLRA was developed through a multi-step process, beginning with a thorough literature review and an examination of existing scales. From those sources, common themes were derived and an initial set of 98 items was developed. Following review by experts with experience in higher-education and student services, several items were deleted or modified. Because the RLRA was intended as a subscale on the SSI, the number of items was substantially reduced to 33, which were then sent to a new group of experts who also had knowledge and skills related to higher education. They were asked to rate each item on a scale of 1 “Not important at all” to 5 “Absolutely essential.” An open-ended question was also included for comments and suggestions. Following data collection, descriptive statistics and z-scores were computed to determine the relative importance of each item. This process resulted in a final instrument of 15 items.
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