“The Relationship between Engineering Students’ Self-Directed Learning Abilities and Online Learning Performances: A Pilot Study” is an article by Pao-Nan Chuo published in 2012 in the Contemporary Issues in Education Research. The primary purpose of the study was to explore the correlation between engineering learners’ self-directed learning abilities and performance in online learning environments. Although there is plenty of research indicating that self-directed learning abilities are closely related with high academic and professional performance, there is a dearth of information focusing on the impacts of engineering students’ self-directed learning abilities, especially in an online learning environment. To investigate this correlation, Pao-Nan Chuo used a sample of 48 students studying electronic engineering and employed Self Directed Learning Readiness Scale (SDLRS) to measure their self-directed learning abilities. In order to minimize the influence of subjects’ background on the study, the researcher used the true experimental design. Participants were required to study 20 web pages unrelated the students’ course of study. Then, the subjects were required to answer 60 multiple test questions in order to measure their learning performance. The data was analyzed using the Pearson Product-Moment Correlation, which tests the correlation of two independent variables. Findings reinforced those of Corbeil (2003): there exists a positive correlation between engineering students’ self-directed learning and online learning performance.
It is commendable that Pao-Nan Chuo relied on SDLRS since it is a reliable measurement of self-directed learning. However, he could have attained more accurate and reliable results had he used the Self-Rating Scale of Self-directed Learning (SRSSDL) since it more detailed. Unlike the SDLRS, the SRSSDL analyses 40 items in 8 critical factors of self-directed learning including awareness, attitudes, motivation, learning strategies, learning methods, learning activities, interpersonal skills, and construction knowledge.
Article 2
In 2011, Wiwat Orawiwatnakul and Sawovapa Wichadee conducted a study titled “A Comparison of Students’ Outcomes In Two Classes: Business Administration Students VS Communication Arts Students Based on Self-Directed Learning Activities.” While acknowledging the importance of self-learning, the researchers aimed to analyze the degree to which self-learning activities can help students acquire language proficiency while enhancing self-directed learning skills. Further, the study recognized that different students had varying learning styles and thus intended to establish which learning strategies could be enhanced by engaging in self-directed learning activities. The researchers hoped to establish, from the findings, effective strategies that could enhance learners’ language skills, motivation, and self-reliance. To conduct this research, the scholars used a sample of 80 ENL students; 40 studying Business Administration (BA) and 40 taking Communication Arts (CA). Participants were required fill a Honey and Mumford’s learning Style questionnaire to establish preferred learning styles, answer a self-directed learning questionnaire, do a pre-test of 50 points analyzing English proficiency levels, participate in a 3-hour self-directed lesson for 12 weeks, then do another post-test of 50 points, and finally answer a questionnaire on personal perspectives of self-directed learning strategies. After applying descriptive and inferential statical procedures, the results established that self-directed learning activities improved the language proficiency of both BA and CA students. Secondly, all learning styles including activist, pragmatist, theorist, and reflector were enhanced by self-directed learning strategies. Surprisingly, self-learning strategies were more beneficial to students of Communication Art than their counterparts in Business Administration.
While the study played a critical role in advancing knowledge related to self-directed learning, there are a number of things that affected the accuracy of the findings. Personally, I would have used a larger sample. The scholars picked only 80 students in a population of 5,445. Secondly, the study did not announce limitations that could have hindered the accuracy of the study. Finally, the researchers did not consider all subjective factors that may influence students’ learning perceptions, styles, and abilities.
Article 3
“A Longitudinal Analysis of the Self-Directed Learning Readiness Level of Nursing Students Enrolled in a Problem-Based Curriculum” is an article by Gulseren Kocaman that aimed to examine the relationship between self-directed learning (SDL) and problem-based learning (PBL). Some scholars such as Hmelo-Siver (2004) and Williams (2001) emphasize that SDL is a primary facet of PBL instruction approach while others state that PBL facilitate SDL. In light of these conflicting results, Gulseren purposed to explore the degree of self-directed learning readiness of nursing students engaged in a problem-based curriculum. In tandem with this, the scholar studied 50 students enrolled in a problem-based nursing school for four years. Participants filled in a Self-Directed Learning Readiness Scale (SDLRS) at the beginning of each academic year and at the end of the longitudinal study. At the end of the study, Gulseren Kocaman analyzed the data using SPSS. All the SDLR scores were analyzed with repeated measures analysis of variance. The researcher applied the Bonferonni correction technique to identify whether there was any superior group. The findings revealed that the nurses’ self-directed learning readiness (SDLR) scores increased each year. Scores at the beginning of the fourth year were higher than those of previous years. Additionally, the results reinforced findings of earlier studies by acknowledging the positive correlation between PBL and SDLR even among engineering students. Additionally, the results showed that students’ acknowledgement of SDL increases with time.
While the researchers indicated that self-directed learning is maturation, they failed to explain the factors that lead to positive outcomes besides facilitators playing a primary role. Additionally, this study failed to compare the performance of learners in this problem-based curriculum with those in more traditional backgrounds. Arguably, may be all students tend to be more self-directed as they progress in their academic years. Finally, SDLR scores tend to be subjective and may this lead to bias.
Proposed research question: what are the individual-based and course-based factors that influence performance levels in a self-directed learning environment? Notably, where there is unanimous consensus among scholars that self-directed learning ability is an important skill in academic and professional settings, and the close relationship between SDL and academic performance, there is a dearth of information on the personal and course-based factors that may facilitate or hinder excellence. There are two supporting facts that support the study of this proposed research question. Firstly, in their article “A Comparison of Students’ Outcomes In Two Classes: Business Administration Students vs. Communication Arts Students Based on Self-Directed Learning Activities,” Wiwat Orawiwatnakul and Saovapa Wichadee found out that self-directed learning activities benefited students of Communication Arts more than their counterparts in Business Administration. This highlights that there are some course-based factors that hinder performance in a self-directed learning environment. Secondly, hdhddhhhdhhd found that, although learners’ SDLR scores improved as one progressed through the academic years, there was no change in scores between the second and third years. This may be because students’ pressure to learn decreases. The SDLR scores them improve in the fourth year as th pressure to perform well in the finals increases. This indicates that there are personal perceptions or beliefs that influence the success of self-directed learning processes.
Hypothesis: Students in non-technical and non-science-based courses record better results while introduced to self-directed learning activities. As the previous research has shown, students in non-technical and non-scientific courses are more willing to embrace new learning strategies than their counterparts in science-based courses. Additionally, the content of non-scientific courses is more flexible. Secondly, science-based learners are fixed to their subject content and learning methods.
