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Hot Off the Press! Secondary At-Risk Students’ Online Course Self-Confidence Levels

Wednesday, October 21, 2015 -- Shane Dennison

We’re very happy to announce that Edmentum’s state and federal programs consultant, Shane Dennison, recently published his first book! Titled Secondary At-Risk Students’ Online Course Self-Confidence Levels,Shane’s publication takes a close look at quantitative research that he performed regarding at-risk high school students’ outcomes in online courses and the role that self-confidence plays in those outcomes. From his research, Shane identified four broad strategies that educators and online content providers can pursue to improve those outcomes:

  1. Align content and materials with the age-appropriate interests of students, particularly for those students in the early secondary grades.
  2. Consistently reinforce to students the importance and future applications of the content they are experiencing online.
  3. Encourage intrinsic motivation for course completion, especially among male students, by presenting courseware and practice activities as an internal challenge for each student based on curiosity and mastery, instead of simply as a task for external rewards or evaluation.
  4. Provide students, especially those in the earlier secondary grades, with comprehensive guides prior to starting any online course that outline what the course will entail, detail measures of success, and offer tips to improve self-confidence. 

Read on for Shane’s overview of recommendations and conclusions from his research for Secondary At-Risk Students’ Online Course Self-Confidence Levels! You can also purchase the book through Lambert Academic Publishing.

Recommendations

Even though overall as a group, the differences in reported student self-confidence levels proved to have no significance, data analyzed did pose possible directions for educators to take. For instance, significant task value differences among age groups were noted, intrinsic goal orientation value differences were prevalent between genders, and finally, self-efficacy for learning and performance level differences proved to be significant across grade levels. Therefore, secondary schools should review how each of these individual constructs are addressed within their online courses.

In order to increase task value among their 14- and 15-year-olds, both educators and online course content providers should make more attempts to have courseware presented in a fashion that has a higher level of interest to that age group (Wilson & Stacey, 2011). Online content providers and online instructors/mentors of this age group should consider making or adding supplements to the content that are more practical to that age group’s interest. Furthermore, teachers and parents should reinforce the importance and future applications of the content they are experiencing online while they are experiencing it or just prior to it (Chiu & Wang, 2008).

A second recommendation surrounds the data showing that the female portion of the sample had a remarkably higher intrinsic goal orientation value than did males. Even though some, or much, of the disparity within this construct could be due to natural psychological and physiological differences among the genders of this age group, certain measures could be taken to help increase male intrinsic goal orientation levels. For instance, online content providers and teachers alike could help increase male levels in this area [intrinsic motivation] by making the courseware present itself as an internal challenge for each student based on curiosity and mastery versus just for external rewards and outside evaluation (Yukselturk & Bulut, 2009). Educators could reinforce this practice and attitudes in students by presenting small chunks of the online courseware to the entire class before they began working on it individually.

A final recommendation revolves around the study data indicating a significant disparity between how each grade level views its own self-efficacy for learning and performance in relation to online education. It was evident that tenth graders had a significantly lower level within this category. Again, both online software providers and teachers can take actions to help improve underclassmen's belief in their own ability to achieve a goal or outcome. Both online content providers and educators should take more steps to positively reinforce successful actions taken by students while proceeding through their online course(s). It would also be logical to state that the underclassmen probably have less online course experience than do the upperclassmen in general. Therefore, a comprehensive pre-online course guide outlining what their online course is about to entail and measures of success expected/needed could help the underclassman improve their self-confidence and how they perceive their abilities going into an online course for the first time (Black, Ferdig, & DiPietro, 2008).

The objective of this study was to expand on prior research that measured whether secondary at-risk students perform significantly better on "learning outcomes" when daily exposure to computer-based instruction is introduced than they do when only traditional classroom instruction is offered (Spradlin, 2009). Also, a key component of this study was to ascertain whether at-risk student perceptions/experiences in relation to self-confidence differ between traditional classroom courses failed and online courses later taken. While this study did expand on previous research, it is still necessary to conduct further research on this focus. Recommendations for further research incorporate a larger sample size, conducting the study in a cross-district capacity that includes multiple high schools versus just one high school within a district. Also, conducting a similar study at a suburban school district in addition to an urban district would be beneficial. Finally, including qualitative questions and/or open response questions within the study apparatus should be considered.

Increasing the sample size would potentially improve the findings of the study. While the response rate was positive, the overall sample size could be an area of concern when compared to the overall population of at-risk students enrolled in online courses across the country. To help increase the sample size(s) of further such studies' multiple high schools within the same district(s) that offer online courses to their at-risk students could be invited to participate (Wadsworth, Husman, Duggan, & Pennington, 2007). The inclusion of more students from multiple high schools would not only be beneficial to the findings but also in regard to students having a variety of teachers and online courseware that may affect their responses one way or the other.

The participants were all enrolled in an online course(s) at an urban high school that has regularly offered online courses to at-risk students needing to make up credits toward graduation over the past few years. Conducting the study with a sub-sample of at-risk students from suburban high schools as well as urban high schools that just recently began offering online courses to at-risk students may give a better indication of how online courses of various formats affect at-risk students’ responses (Journell, 2007). Additionally, having a standard rule that all potential participants have never experienced an online course prior to the study could benefit in relation to more conclusive findings.

One additional recommendation for further research is to include qualitative questions to the survey. The quantitative questions on both the pre- and post-online surveys asked students to rank where they felt they belonged in regard to each type of theoretical self-confidence construct offered by using a rather strict Likert scale set of choices. The inclusion of qualitative questions would have given participants the opportunity to explain how one or more of the interactions with the online course(s) they completed influenced their perceived self-efficacy levels and/or grade and completion level experiences (Morris & Finnegan, 2009).

Conclusions

This study was undertaken to answer the following research questions:

Ql. What are the differences between the Motivated Strategies for Learning Questionnaire (MSLQ) scores for "self-efficacy for learning and performance" at the beginning of an online course and at the end of an online course among at-risk students?

Q2. What are the differences between the MSLQ scores for "control beliefs" at the beginning of an online course and at the end of an online course among at-risk students?

Q3. What are the differences between the MSLQ value component scores for "intrinsic goal orientation," "extrinsic goal orientation," and "task value" at the beginning of an online course and at the end of an online course among at-risk students?

Q4. What are the differences between the MSLQ scores for "test anxiety" at the beginning of an online course and at the end of an online course among at-risk students?

Q5. What are the differences between MSLQ scores at the beginning of an online course among at-risk students based on age, sex, and grade level?

Q6. What indicators will a linear regression model reveal between online technologies self-efficacy for learning and performance, control beliefs, intrinsic goal orientation, extrinsic goal orientation, task value, test anxiety, demographics, and student satisfaction variables to predict grade performance and completion levels in an online course?

This study was to expand on research that measured differences between MSLQ constructs in relation to students' feelings prior to taking an online course(s) and after completing an online course(s). The purpose of this non-experimental quantitative study was to determine whether secondary at-risk students perform significantly better on "learning outcomes" when daily exposure to computer-based instruction is introduced than they do when only traditional classroom instruction is offered. Also, a key component of this study was to ascertain whether student perceptions/experiences in relation to self-confidence differ between traditional classroom courses failed and online courses later taken.

Results of this study indicated that, in general, there were no statistically significant differences in students' self-efficacy for learning and performance, control beliefs about learning, intrinsic or extrinsic goal orientations, task values, and test anxiety prior to beginning an online course(s) and after completing an online course(s). Yet, in regard to task value, the null hypothesis was rejected in relation to response differences among the four age groups part of sample. It could logically be concluded that 15-year-olds had lower task value levels than did the 16-, 17-, and 18-year-olds part of this study. Thus, the 15-year-olds did not perceive course material as interesting or important as the 16-, 17-, and 18-year-olds did. Furthermore, in respect to intrinsic goal orientation, the null hypothesis was rejected in relation to response differences among the two gender groups part of this study. It could logically be stated that females had higher intrinsic goal orientation than did the males. Thus, it could be concluded that females proved to have a higher concern for participating within courses for the sake of curiosity and being challenged versus just receiving a reward of a good grade. Moreover, concerning self-efficacy for learning and performance, the null hypothesis was rejected in relation to response differences among the three grade levels part of this study. It could logically be concluded that tenth graders had lower self-efficacy for learning and performance levels than did the eleventh and twelfth graders part of this study. Hence, the tenth graders had noticeably less belief in their own abilities to achieve a goal or an outcome than did the eleventh and twelfth graders.

Finally, when analyzed in its entirety, the dependent variable of course grades and course completion levels was not significantly impacted by any of the MSLQ variables across any independent demographic variable. Though gains were reported in both grades and completion levels from traditional courses the students took earlier, no statistical significance in respect to using MSLQ constructs as predictors to gains in these areas could be assumed. Though not significant as a whole, noticeable differences were evident between MSLQ constructs introduced and demographic groups. The 16-, 17-, and 18-year-olds did report more consistently that they had somewhat better grades in their online version of a course(s) then did the 15-year-olds. With respect to gender, both females and males had nearly identical means that were almost exactly at the "somewhat better" selection when responding to how their grades and completion levels were in comparison to the same course they took previously in a traditional format. All grade levels reported somewhat higher grade and completion levels on their online version of course(s) taken previously in a traditional format.

Practical application recommendations from the study results, such as online courseware providers and teachers working to make courseware presented in a fashion that has a higher level of interest to specific age groups, are feasible. Also, online content providers and teachers alike could help increase male intrinsic goal orientation values by making the courseware present itself as an internal challenge for each student based on curiosity and mastery versus just for external rewards and outside evaluation. Moreover, both online software providers and teachers can take actions to help improve underclassmen's belief in their own ability to achieve a goal or outcome.

Further research is recommended by incorporating a larger sample size and conducting the study in a cross-district capacity that includes multiple high schools versus just one high school within a district. Also, conducting a similar study at a suburban school district in addition to an urban district would be beneficial. Finally, including qualitative questions and/or open response questions within the study apparatus should be considered.

The research that Shane put into this publication is an important piece of the larger body of work regarding high school graduation rates and dropout prevention that so many in the education world are engaged in. It’s also a great representation of the expertise and dedication of our Edmentum employees! We could not be more proud of the innovative work they are engaged in every day to provide effective solutions for our customers and continuously improve our products.

Interested in learning more about Edmentum’s solutions for online learning? Check out this brochure to find out how we’re moving education forward!