Fostering Self-efficacy for Biblical Learning and Doctrinal Awareness with Micro-teaching in a Brief Course on Bible Study

Self-efficacy for biblical learning was explored in the context of a small group experience focused on how to study the Bible. After first developing a new instrument to measure self-efficacy for biblical learning in a pilot study, ten church attendees participated in a seven-week course designed around the hermeneutical principles of understanding a Scripture passage in textual and historical context, placing the passage in the grand story of God, and relating it to relevant doctrine. The small group process employed micro-teaching as a mechanism to facilitate challenge and mastery experience in learning. Micro-teaching places the student in the role of teacher for very short segments of the class. It was hypothesized that this elevation of the student role would facilitate stronger self-efficacy beliefs for biblical learning and increase doctrinal awareness. Results demonstrated considerable improvement in both self-efficacy and doctrinal awareness across multi-methods. Positive change in teaching confidence and accuracy ratings was also observed for participants’ micro-teaching, which points to the process as a mastery experience. Because self-efficacy beliefs are excellent predictors of future behavior, increased efficacy for biblical learning could lead to increased engagement with the Bible. Implications for future research and practical ministry are discussed, including elevated involvement of congregants in Bible study classes and increased focus on hermeneutical skills

Strengthening the Campus Leadership Team through Effective Principal and Counselor Relationships: Implications for Training

Campuses with successful leadership teams have a better opportunity to meet the ever-increasing and complex needs of the students they serve (Crowther, Kaagan, Ferguson, & Hann, 2002). These successful campuses are strengthened when they include strong principals and counseling teams with shared mutual trust and understanding that permeates the school climate (DeVoss & Andrews, 2006). A review of the literature revealed a paucity of studies examining the nature of successful principal-counselor relations and the impact of this relationship on student success, effective campus leadership teams, and an effective school climate that promotes learning. Meaningful dialogue and discussion of this critical professional relationship also were found lacking in the major counseling and educational leadership professional journals

Not All Effects Are Created Equal: A Rejoinder To Sawilowsky

In the continuing debate over the use and utility of effect sizes, more discussion often helps to both clarify and syncretize methodological views. Here, further defense is given of Roberts & Henson (2002) in terms of measuring bias in Cohen’s d, and a rejoinder to Sawilowsky (2003) is presented

Bias and Precision of the Squared Canonical Correlation Coefficient Under Nonnormal Data Condition

Monte Carlo methods were employed to investigate the effect of nonnormality on the bias associated with the squared canonical correlation coefficient (Rc2). The majority of Rc2 estimates were found to be extremely biased, but the magnitude of bias was impacted little by the degree of nonnormality

The Assumption of a Reliable Instrument and Other Pitfalls to Avoid When Considering the Reliability of Data

The purpose of this article is to help researchers avoid common pitfalls associated with reliability including incorrectly assuming that (a) measurement error always attenuates observed score correlations, (b) different sources of measurement error originate from the same source, and (c) reliability is a function of instrumentation. To accomplish our purpose, we first describe what reliability is and why researchers should care about it with focus on its impact on effect sizes. Second, we review how reliability is assessed with comment on the consequences of cumulative measurement error. Third, we consider how researchers can use reliability generalization as a prescriptive method when designing their research studies to form hypotheses about whether or not reliability estimates will be acceptable given their sample and testing conditions. Finally, we discuss options that researchers may consider when faced with analyzing unreliable data

Performance Evaluation of Confidence Intervals for Ordinal Coefficient Alpha

The aim of this study was to investigate the performance of the Fisher, Feldt, Bonner, and Hakstian and Whalen (HW) confidence intervals methods for the non-parametric reliability estimate, ordinal alpha. All methods yielded unacceptably low coverage rates and potentially increased Type-I error rates

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses

Key Challenges and Some Guidance on Using Strong Quantitative Methodology in Education Research

Article reviews several common areas of focus in quantitative methods with the hope of providing guidance on conducting and reporting quantitative analyses. The review addresses causal inferences, measurement issues, handling missing data, testing for assumptions, dealing with nested data, and providing evidence for outcomes

Quantitative Preparation in Doctoral Education Programs: A Mixed-Methods Study of Doctoral Student Perspectives on their Quantitative Training

Aim/Purpose: The purpose of the current study is to explore student perceptions of their own doctoral-level education and quantitative proficiency. Background: The challenges of preparing doctoral students in education have been discussed in the literature, but largely from the perspective of university faculty and program administrators. The current study directly explores the student voice on this issue. Methodology: Utilizing a sequential explanatory mixed-methods research design, the present study seeks to better understand doctoral-level education students’ perceptions of their quantitative methods training at a large public university in the southwestern United States. Findings: Results from both phases present the need for more application and consistency in doctoral-level quantitative courses. Additionally, there was a consistent theme of internal motivation in the responses, suggesting students perceive their quantitative training to be valuable beyond their personal interest in the topic. Recommendations for Practitioners: Quantitative methods instructors should emphasize practice in their quantitative courses and consider providing additional support for students through the inclusion of lab sections, tutoring, and/or differentiation. Pre-testing statistical ability at the start of a course is also suggested to better meet student needs. Impact on Society: The ultimate goal of quantitative methods in doctoral education is to produce high-quality educational researchers who are prepared to apply their knowledge to problems and research in education. Results of the present study can inform faculty and administrator decisions in doctoral education to best support this goal. Future Research: Using the student perspectives presented in the present study, future researchers should continue to explore effective instructional strategies and curriculum design within education doctoral programs. The inclusion of student voice can strengthen and guide future work in this area

Reliability generalization for the Motivated Strategies for Learning Questionnaire: A meta-analytic view of reliability estimates

A reliability generalization meta-analysis was performed to explore the relationship between study factors and levels of alpha reliability for the 15 subscales of the Motivated Strategies for Learning Questionnaire (MSLQ). The MSLQ has been widely adapted over the past 25 years to investigate the role of motivation and strategies in learning, primarily at the postsecondary level. A literature search from the years 1991 to 2015 yielded 295 peer-reviewed journal articles and 1,369 alpha reliability coefficients. Articles were coded for six potential moderator study variables. A novel varying coefficient (VC) model was adopted to determine average reliabilities across studies for each subscale and to perform multiple regression analyses to identify study variables that may moderate alpha reliability estimates. Commonality analyses were used to aid in interpretation of regression results. Meta-analyzed alpha reliabilities were lower than values published in the test manual for all but three of the subscales. Ability of specific moderators to predict score reliability varied across subscales; however, studies in North America, in English, or using a 7-point response scale generally corresponded to increased reliability estimates. Knowledge of expected levels of score reliability under varying sample and study conditions may provide useful information for researchers planning future use of the MSLQ