Maximizing E-learning ROI: Self-Regulated Learning and Employee Performance

Advances in online technologies in the past two decades have made it possible for many organizations to incorporate online learning into their training and development programs.  In doing so, new and existing employees were encouraged to access portion or most of their training materials online. Traditionally, the growth of online technologies is based on the expectation that technologically enhanced settings would significantly influence employee performance in workplace. However, very little is known about the motivational, cognitive, and behavioral attributes that may influence employee performance in online settings. An organization that is proficient in identifying these attributes will prosper and succeed.

When conducting a need assessment analysis, some organizations tend to overlook the influence of self-regulation on performance outcomes. Employee performance is one ‘contributing factor’ that can have a significant impact on organizational success. The performance of any organization is directly associated with the degree to which the organization helps individual employees develop their capacity (e.g., skills, knowledge, abilities, and attitudes, etc.) to complete tasks in a competent way.

Self-regulated learning is one skill that organizations cannot afford to ignore.  In fact, strengthening employee’s self-regulation would directly or indirectly improve all the other skills necessary for successful performance in the workplace (If you are not familiar with the concept of self-regulation, please see my previous posts).  The role of self-regulation becomes even more important when e-learning is part of the training curriculum. Many individuals are simply not equipped enough to exercise high degrees of self-regulation in online or blended environment.

Studies examining the role of self-regulation have consistently indicated that successful performance in work place or academia is directly associated with individual’s ability to exercise high degrees of self-regulated learning. Self-regulation is simply one of the most important predictors of success in online, face-to-face, or blended learning environments.  Yes, it is even more important than IQ.  Future posts will discuss the relationship between IQ and self-regulation in more details. This post will only focus on the manner in which self-regulated learning can influence one’s performance in the workplace.

Although there is a growing body of research on the role of self-regulation in online environments, there are very few studies that have examined the motivational and cognitive components of self-regulation in blended settings (Bernard, Lan, To, Paton, & Lai, 2009; Lynch and Dembo, 2004; & Orhan, 2007).

Researchers have consistently found that self-regulatory dimensions of self-efficacy, intrinsic goal orientation, help seeking, and time and environment management tend to play a significant role in online learning environments (Bell & Akroyd, 2006; ; Joo et al., 2000; Kitsantas & Chow, 2007; Radovan, 2011; Vaughan, 2007; Xie, Durrington, and Yen, 2011). A description of the findings for each of these domains follows.

Self-efficacy and Online Learning

Pintrich (1990) defined self-efficacy as “judgment about one’s ability to accomplish a task as well as one’s confidence in one’s skills to perform that task”.  As stated by Peterson and Arnn (2005) in Hodges (2008), the quality of performance is significantly associated with their levels of self-efficacy. Research examining the role of self efficacy in face-to-face settings has consistently found self-efficacy to be one of the most important predictors of academic success for face-to-face students (Linnenbrink & Pintrich, 2003; Pintrich, 2004; Zimmerman, 2002; Zimmerman, Bandura, & Martinez-Pons, 1992). For example, Zimmerman et al. (1992) examined the causal role of students’ self-efficacy beliefs and academic goals in self-motivated academic attainment. Using a path analysis, Zimmerman and his colleagues found self-efficacy to be a strong predictor of academic achievement and student goals. Self-efficacy accounted for a substantial 31% of the variance in predicting academic grades.

Although the concept of self-efficacy has been extensively studied in traditional learning environment, very few studies have examined the role of self-efficacy in online learning environments. Research examining the role of self-efficacy in an online environment is mixed.  For example Joo, Bong, and Choi (2002) examined the influence of academic self-efficacy on the academic performance of students enrolled in web-based portion of a science course.  Students were instructed to attend web-based instruction sessions once a week for three weeks during their traditional science courses. Students` academic performance was measured using a written and an internet based exam. Although students` self-efficacy predicted their performance on the written exam, it did not appear to influence their performance on the internet-based exam.  Bell and Akroyd (2006) found that online students` level of expectancy, which is an important component of self-efficacy (Pintrich, 2004), was a positive predictor of academic success in online learning settings.

Even though previous research has found self-efficacy to be one of the most important determinants of academic success in students, it is noteworthy to mention that self-efficacy is a situation-specific phenomenon which appears to vary from one context to the next (Hodges, 2008).  Another motivational construct that works closely with self-efficacy is intrinsic goal orientation (Pintrich, 1999, & 2004; Zimmerman 2002, 2008). The next post will examine the   role of intrinsic goal orientation in online learning environment.

* Please Note: I will be adding a separate page for all the references. 

This entry was posted in Corporate Training, E-Learning, Higher Education, Needs Assessment and Evaluation, Online Learning, Self-Regulated Learning, Technology and tagged , , , , , . Bookmark the permalink.

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