Pedagogical Innovations Journal Club Articles 2015-2016

June 2016

Join the Center for Educational Innovation for Pedagogical Innovations Journal Club on Tuesday, June 21st at 11:30 in Room 444 UOffP.  Each month we present a different journal article describing a pedagogical innovation that may spark ideas for teaching. This month we will discuss the article “Aesthetics and e-assessment: the interplay of emotional design and learning performance published in 2011 in Distance Education.  Aesthetic design refers to “careful orchestration of available design elements to provide a heightened and lasting experience for learners”. In this article the authors looked at the effect of aesthetic design on student performance in an online course. They created two separate assessment environments with identical material. One was designed following principles of aesthetic design. The other did not consider aesthetics in its’ design. Both were designed for utility and usability. Students were randomly assigned to one of the two groups. Students in the environment designed with aesthetic principles showed increased task performance, participant satisfaction, willingness to continue use, and decreased participant cognitive load when compared to the low aesthetics environment. We will discuss these aesthetic design elements and the implications of these results for teaching. Thanks to Katherine Brink in CSOM for finding and suggesting the article. You do not have to read the article to benefit from attending the journal club.  Bring your lunch; dessert will be served. 

May 2016

May's article was How do online course design features influence student performance?” published in 2016 in Computers and Education.  This paper aims to identify course design practices that correlate with improved student performance in online classes. To identify the potential practices to examine, the authors referred to Quality Matters and looked at the published research on good practices for online teaching. From these resources the authors identify four general categories for course design: 1) course organization and presentation, 2) learning objectives and assessments, 3) interpersonal interaction, and 4) technology. The authors created rubrics to evaluate each of these categories in 23 online courses, looking for correlation between courses that scored high in one or more of these four categories and student grades. It was found that interpersonal interaction was the only category that correlated with improved student grades. Focus groups of student participants in the courses provided feedback to identify the techniques and approaches used by instructors for promoting interpersonal interaction. Those approaches are summarized in the article.

April 2016

In April,  we discussed the article Teaching critical thinking” published in 2015 in the Proceedings of the National Academy of Sciences.  This paper describes an intervention designed to improve student critical thinking. The intervention asked students to compare their collected data sets to other data sets and to models and to act on those comparisons. It was found that these students were much more likely to engage in measured critical thinking behavior than students in a control group who did not receive this training. This result continued after the training was discontinued. Though the students were in an introductory physics laboratory course the authors propose that this intervention could be successful in any course that asks students to work with data and models. We will discuss the implications of these results for teaching. You do not have to read the article to benefit from attending the journal club.  Bring your lunch; dessert will be served. 

March 2016

In March, we discussed the article “Promoting engagement in online courses: What strategies can we learn from three highly rated MOOCS” published in 2016 in the British Journal of Educational Technology.  In this study, the authors looked at student comments about three high-rated MOOCs to identify common elements that may be used as a good practice guide for designing future online courses. In examining the comments from 965 student participants, five general qualities emerged. 1. The courses emphasized problem-oriented learning with clear and comprehensive explanations. 2. The instructors were accessible and passionate about their subject. 3. There were opportunities for interacting with peers. 4. The courses employed active learning.  5. The courses provided resources to address participant learning needs. 

February 2016

 “Conceptions of Effective Teaching and Perceived Use of Computer Technologies in Active Learning Classrooms”   In this study, the authors examined how instructor’s conceptions of what constitutes effective teaching correlated with their use of computer technologies in an Active Learning Classroom. Qualitative studies identified three different categories of descriptions of effective teaching held by instructors. Those categories were teacher-centered, engagement-centered, and learner centered teaching approaches. They found that instructor’s use of computer technology in the ALC fell into four general categories: 1. Transmitting knowledge 2. Student support 3. Tools for learning and student development and 4. Having a limited role in student learning. These categories of use correlated with the instructor’s conceptions of effective teaching. 

January 2016

The Impact of Findability on Student Motivation, Self-Efficacy, and Perceptions of Online Course Quality”. In this study the authors looked at the effect of ease-of-findability of important items in an online course on student’s self-efficacy and their motivation and perceptions of the online course. The experiment divided students into random assignments of a mock online course that was of high findability (easy to find important course components like the syllabus and grading policy) or was of low findability (difficult to find important course components). They found that students in the low-findability group rated their self-efficacy, motivation to take the course, and opinion of the course and instructor significantly lower than the students in the high-findability group. 

December 2015

How Video Production Affects Student Engagement: An Empirical Study of MOOC Videos”. This study looks at student video-watching behavior from 6.9 million video watching sessions from four different MOOCs produced by MIT, Harvard, and Berkeley. The authors use this data to make recommendations for creating videos for improved student engagement.  Among other results, they find that shorter videos are better than longer videos, with six minutes or less being the optimal length for increased student engagement. An instructor speaking more rapidly results in more engagement than one with a slower rate of speaking. Furthermore, high production value videos don’t seem to be important for student engagement. 

November 2015

Closing the social-class achievement gap: a difference-education intervention improves first-generation students’ academic performance and all students’ college transition” This study looks at a randomized controlled intervention program designed to improve the success of first-generation college students. The program involved senior college students sharing their real-life stories including their own background as either a first-generation or continuing-generation student with incoming freshmen. They found that students in the intervention group had a significantly higher end-of-year GPA than the control group.

October 2015

“The International Student Density Effect: A profile of a global movement of talent at a group of major U.S. universities”
This study examined data collected in a recent Student Experience in the Research University (SERU) Consortium survey. Specifically the authors looked at socio-economic background, motivations, behaviors, and levels of satisfaction for both US and International Students (IS) at 15 different universities including the University of Minnesota.  They categorized the 15 schools as Low, Medium, or High Density for the number of IS, and use this data to look for correlations with several different educational outcomes. High Density IS universities (of which the Uof M is one) correlate with both positive and negative outcomes, suggesting opportunities and challenges for classroom learning.

August 2015

“Impact of Cold-Calling on Student Voluntary Participation” 
This study examined the effects of cold-calling (calling on students whose hand is not raised) on voluntary class participation and comfort with participation.  The authors found that students in classes where the instructor used more cold-calling are more likely to volunteer an answer, answer more questions over time, and express more comfort participating in class discussions. This counterintuitive result suggests that cold-calling may be an effective technique to engage more students in discussion. 

July 2015

“Less teaching, more learning: 10-yr study supports increasing student learning through less coverage and more inquiry” 
This study examined and quantified the effects of changing an introductory biology traditional cookbook laboratory format to an inquiry format over a period of 10 years. The authors measured a decrease of over 40% in content coverage over the study period and looked for effects of that content decrease on both student learning and student opinions about the course. Students in the increased inquiry learning plus decreased content coverage conditions displayed more content knowledge and more positive opinions than students with more content coverage.

June 2015

"Are All Interventions Created Equal? A Multi-Threat Approach to Tailoring Stereotype Threat Interventions"  
Stereotype threat ("a concern that one's actions can be seen through the lens of a negative stereotype") has been shown to negatively impact student performance. Helpfully, interventions have been developed to protect against stereotype threat. The authors explore whether there is a one-size-fits-all approach or if interventions should be matched to the type of stereotype threat; threat to self or threat to group. Their data shows that interventions tailored to the type of threat are effective, while interventions that are not, are not effective.