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This study examines the effect of using a computerized decision aid on student cognitive effort and learning in the first tax course. Students at a mid-western university in the United States prepared a 1040 tax return using either paper or tax software from a given set of taxpayer information. Students using paper forms reported higher levels of cognitive effort than did students using the tax software, however, no association between self-efficacy and cognitive effort was found. A test for association between decision aid type and inferential (higher-level) learning (the third level of Bloom's taxonomy) found cognitive effort to be statistically significant. The study also found a significant interaction between cognitive effort and experience. These results suggest that paper forms, which require students to work through task processes, may be better instructional tools for helping students acquire a deeper understanding of subject matter. Although tax software provides potential benefits of increased accuracy and speed, practitioners should be aware of its limitations as a learning tool.

We examine how school districts in California help their high schools respond to state accountability requirements. We discovered two contrasting forms of district interventions: those aiming to increase schools’ internal coherence and those encouraging direct but narrower responses to state requirements. Drawing on interviews in six districts and eight high schools, we find that many district efforts focus on immediate responses to state requirements to raise test scores. Yet, our analysis suggests that without strong district efforts to increase internal coherence, interventions aimed at eliciting school responses will be less beneficial over time.

We use student-level online resource usage data for students in four different introductory accounting courses to explore the impact on exam performance of both student study effort and students’ revealed preferences for reading text or watching video lectures. The online learning tool tracks student study choice (read text, watch video, or skip) on a paragraph-by-paragraph level. We match these usage data with student performance on course exams. We find that students who study more material earn higher exam scores than do students who study less material. We also find that students who self-select to do relatively more of their studying through reading text score higher on exams, on average, than do students who self-select to do relatively more of their studying through watching videos. Specifically, holding the overall amount of study constant, a student who chooses to spend the highest fraction of her or his study time watching video mini lectures earns exam scores 10 percentage points lower (six-tenths of a standard deviation) than a student who chooses to spend the lowest fraction of study time watching videos. Our results demonstrate that at least for introductory accounting students, increased study effort does indeed have a positive impact on exam performance. Our evidence also suggests that the highest performing introductory accounting students choose to learn accounting proportionately more through reading than through watching. These results are a reminder that when we talk about using “technology” to help our students learn accounting, the written word is still an important technology.

I address the question, Is theory useful when collaborating with teachers to improve student engagement?

We based our work on four principles of motivation drawn from the research literature: students are more likely to engage in learning if teachers support their perceptions of competence, autonomy, belongingness, and make learning meaningful. To bridge the gap between theory and practice, we suggested that teachers use certain instructional strategies, like open-ended questions, related to supporting student engagement. These strategies were both more complex than the standard practices and more challenging to implement, given the current U.S. emphasis on standardized testing. In two longitudinal studies, we provided rationales for engagement principles and instructional strategies related to student engagement and encouraged teachers to use new practices. Mixed methodology included online observation measures and video of classroom instruction, retrospective interviews with teachers, and student interviews and experience sampling self-reports.

Short case studies of teachers change illustrate the examples of implementation. In both studies, about half the teachers made significant instructional changes, which were related both to teacher perceptions of student engagement and to student self-reports.

Insights gained from the studies may offer researchers practical information about how to work with teachers to improve engagement in the classroom. They include whether teachers can understand abstract motivation terminology, consider students’ “basic needs” when planning instruction, and implement strategies so that they are likely to support student engagement. Other learnings include the strong impact of teacher culture on change efforts and the need to consider teachers’ “basic needs” if we are to support them in instructional change. Long-term collaboration and establishing mutual trust may be the best way for both researchers and teachers to develop common understandings for supporting student motivation in the classroom.

Research over the last decade or so has made it clear that quality teachers matter to student achievement. What is less clear is the ways in which they matter and how we can prepare such high-quality teachers. Nowhere is this lack of clarity more evident than in special education, where we have few studies on teacher quality and even fewer studies on the type of preparation opportunities that would lead to high quality. Thus, it is difficult to make evidence-based decisions about how quality special education teachers should be defined and prepared. As a field, we have to turn to research in general education to provide a sense of some of the dimensions of teacher quality and effective teacher education. In this chapter, we provide a summary of the research on characteristics of highly qualified teachers and what we know from the research on teacher education and professional development that might foster these qualities, both in general and in special education. Part of our discussion centers on the concerns surrounding this body of research and the challenges of applying the findings to the field of special education. Although these challenges pose considerable problems, we are optimistic that potential solutions exist and can be reached through an alignment of initial teacher education and induction.

Although much attention has been devoted to the study of accounting students’ performance, little attention has been shown to the process of accounting students’ performance. Attention to process necessitates that the subject of accounting students’ test-taking behavior be explored. This study invites attention to the amount of time students take to return their examinations. Time spent on this critical task can be understood as a measure of student ambition to do well, student preparation or cognitive engagement. Using data collected from many classes taught by several instructors at one selective private institution, the results suggest that there is a non-linear relationship between the order in which exams are returned and exam performance. Specifically, those who work on their exams for longer tend to score lower. However, those that return their exams relatively quickly do not necessarily score better. The middle range, wherein students complete their exams neither early nor late relative to others, is associated with better test performance. The relationship between exam return order and test performance also varies by the type of exam and by the matriculation level. The study offers to add to our understanding of accounting students, an achievement that may be an underappreciated prerequisite to effective instructional outcomes.

The growing body of research on student engagement in online writing courses suggests that learning management system (LMS) technology does not by itself create an interactive learning situation nor does it automatically engage students in meaningful interactions with their peers and the instructor. Traditional top-down engagement strategies such as a discussion forum, we argue, have not worked to increase student-to-student engagement in the online environment, confirming our contention that students’ notions of engagement and quality are different from instructors’. Engagement should be re-envisioned as a student-centered effort, wherein educators take on the responsibility of implementing strategies that promote student-to-student engagement. This chapter, then, reconceptualizes approaches to student engagement in online writing-intensive classes. It examines how virtual learning environments challenge traditional notions of student engagement, offers some innovative learner–instructor engagement strategies that can be marshaled to improve student learning, and addresses the challenges and successes of this undertaking, in an effort to establish a meaningful and sustainable student-centered online writing classroom.

This chapter highlights the creation of a STEM Center of Excellence for Active Learning (SCEAL) at North Carolina Agricultural and Technical State University. The overarching goal of the STEM Center is to transform pedagogy and institutional teaching and learning in order to significantly increase the production of high-achieving students who will pursue careers and increase diversity in the STEM workforce. Some of the STEM Center’s efforts to reach its goals included supporting active learning classroom and course redesign efforts along with providing professional development workshops and opportunities to garner funding to cultivate student success projects through the development of an Innovation Ventures Fund. Outcomes from this Center have led to several publications and external grant funding awards to continue implementation, assessment, and refinement of active learning innovations and interventions for STEM student success for years to come.

Despite many well-intentioned efforts to improve student achievement in chronically low-performing schools, there is little evidence of significant progress. A new and different kind of data; however, is providing a fresh perspective on the problem: According to recent studies, research-based instructional strategies – those strategies that have been proven to increase the likelihood that students will be able to retain, recall, and apply what they have been taught – are not consistently used in classrooms. Irrespective of the many changes that occur in schools, student achievement will not significantly improve until teachers consistently use and school leaders consistently promote research-based instructional strategies. The purpose of this chapter is to prepare school leaders to assess the use of research-based instructional strategies in their school, and then use the data to promote more effective instruction. This chapter will provide user-friendly tools and strategies for collecting, organizing, and analyzing classroom observation data; case studies; sample data sets; findings and conclusions drawn from sample data tables; a step-by-step process for collecting the data; samples of research-based instructional strategies; and references for identifying research-based instructional strategies.