Course Design
FLIPPED PSYCHOLOGY STATISTICS COURSE: A FIELD EXPERIMENT
A unique and nontraditional course was developed and administered to undergraduate students at a large, public, liberal arts university. The course was for Psychology Statistics and its structure fol-lowed a blended learning model that essentially flipped traditional homework with in-class work.
The new course structure was designed to achieve a learner-centered environment, where the focus was on the student rather than the material being taught.
Students viewed lectures online at home rather than passively learning in class. The lectures were video recordings of the two instructors that were then uploaded to a university webpage dedicated to the course. A lecture was generated for each of the major sections of the chapters in the textbook.
PowerPoint slides were also created that accom-panied each lecture. Students printed the slides and were encouraged to make note of questions or points of confusion to be discussed with the profes-sor during face-to-face time. Viewing lectures at home created time in-class to work on problem sets that would normally be completed as homework assignments. They consisted of 15 multiple-choice questions, five open-ended questions, and 10 true or false questions. Answers to the questions were provided to students in the study guide. This al-lowed for immediate feedback to students on their performance, but also offered the opportunity for students to cheat. To circumvent this temptation and to foster deep processing of conceptual statistics understanding, students were required to elaborate on why the chosen answer was correct. Problem
sets were turned in each week and students were required to show all work including an explanation of the correct answer for each problem.
A second unique aspect of the new structure was the focus placed on diversity inclusion into the curriculum. “Application days” were scheduled throughout the course where students applied the statistical principles they learned to real world situ-ations related to social justice issues. For example, a guest faculty member presented research related to gender equity. On another application day, a graduate student presented research related to race discrimination. Students read articles written by the guest speaker’s prior coming to class. Class time was then devoted to understanding the researcher’s social issue and analysis of some of the speaker’s data. Furthermore, a final course project required students to analyze quantitative information stu-dents collected regarding a social justice topic of their choice in which there was a “pro” side and a
“con” side. The projects were shared with the class during a poster presentation session that modeled that of psychology professional conferences. In addition, students were individually responsible for writing a short American Psychological As-sociation (APA) style manuscript describing their study, analyses, and results.
Method Participants
Participants included undergraduate students at a liberal arts state university in the Northeast en-rolled in Psychology Statistics courses (i.e., two flipped courses and two traditional courses). See Table 1 for participant demographics.
Materials and Procedure
Students completed a series of surveys at the be-ginning of the semester and again at the end of the semester. The first instrument was the Survey of Attitudes towards Statistics Scale (SATS; Schau,
Promoting Active Learning through a Flipped Course Design
Stevens, Dauphinee, & DelVecchio 1995, Schau, 1999). The SATS assesses four components of at-titudes toward statistics. These include affect (e.g., positive and negative feelings about statistics);
cognitive competence (e.g., students’ intellectual knowledge and skills when applied to statistics);
value (e.g., usefulness, relevance, and worth of statistics in personal and professional life); dif-ficulty (e.g., difdif-ficulty of statistics as a domain).
Items are answered on a 7-point Likert scale. In this study, pre and posttest Cronbach alphas for each subscale were .85 and .91 for affect, .89 and .89 for cognitive competence, .85 and .87 for value, and .82 and .79 for difficulty.
The second instrument the students completed was the Cultural Sensitivity Scale (Chen & Starosta, 2000). This scale consists of 24 items that measure six affective elements of intercultural sensitivity, includ-ing self-esteem, self-monitorinclud-ing, open-mindedness, empathy, interaction involvement, and suspending judgment. An overall score is computed from this assessment with a higher score indicating higher levels of sensitivity in intercultural interactions (Chen
& Starosta, 2000). Pre and posttest Cronbach alphas for the current study were found to be .97 and .72.
The third measure was an assessment of statisti-cal content knowledge. This assessment consisted of 14 multiple-choice items that were developed by a
faculty member who was considered an expert in psy-chology research and statistics. The faculty member was blind to the hypothesis of the study, thus creating an objective assessment strictly on the material in the textbook. In addition, all of the instructors were prohibited from seeing the assessment until after the study was complete. The assessment was scored for number of correct answers and was given to students at the beginning and end of the semester.
Differences between Course Structures on Outcome Measures To understand how course structure, pretest scores (i.e., statistics knowledge, ISS, and SATS), and posttest scores (i.e., statistics knowledge, ISS, and SATS) the following analyses were performed. First, ANOVAs were performed to determine whether there were group differences on any of the pretest and posttest scores. Although there were no significant differences on pretest scores between groups, there were differences in the mean scores suggesting possible confounds (see Table 2). Specifically, the students in the flipped course scored slightly higher than the students in the traditional course on a number of the measures. Looking at just posttest scores, those in the flipped course scored significantly Table 1. Participant demographics
Hybrid (n = 50) Traditional (n = 59)
Mean Age (SD) 19.04 (.90) 19.44 (2.46)
Gender (%)
Promoting Active Learning through a Flipped Course Design
higher on statistical knowledge (F(1, 107) = 7.092, p = .009, ƞp2 = .062) and the Intercultural Sensitivity Scale (F(1, 107) = 6.026, p = .016, ƞp2
= .062) at the end of the semester. All other dif-ferences were not significant. Next, a MANCOVA was performed to examine whether controlling for the initial slight confounds between course structure and pretest scores changes the posttest scores across the course structures. After con-trolling for pretest scores, statistical knowledge at the end of the semester was still higher in the flipped course (F(1, 101) = 4.256, p = .042, ƞp2 = .040), however scores on the ISS were no longer significantly different (F(1, 101) = 3.238, p = .075) and no other significant differences were revealed.
Exploratory Results
Exploratory analyses were also performed to examine whether demographic differences exist.
No significant differences were found for gender.
Looking at year in school, significant differences were found for a number of pretest scores using ANOVAs and post hoc Tukey tests (see Table 3).
Generally, first year students were significantly higher on intercultural sensitivity (F(3, 105)
= 15.547, p < .001, ƞp2 = .314), SATS: affect (F(3, 105) = 4.228, p = .007, ƞp2 = .112), SATS:
cognitive competence (F(3, 105) = 2.908, p = .038, ƞp2 = .076), and SATS: difficulty (F(3, 105)
= 4.007, p = .010, ƞp2 = .103). Similar analyses were performed to examine group differences on posttests revealing significant differences for SATS: cognitive competence (F(3, 105) = 2.796, p = .044, ƞp2 = .075) and trends for SATS: affect (F(3, 105) = 2.527, p = .061, ƞp2 = .066) and SATS: difficulty (F(3, 105) = 2.261, p = .086, ƞp2 = .070), with third year students scoring significantly higher than second year students on affect and cognitive competence and fourth year students tending to score higher than others on difficulty.
Table 2. Mean scores on pretest and posttest measures for each statistics course
Flipped (n = 50) Traditional (n = 59)
Stat Knowledge Pre
Post* 9.12
16.04 8.22
14.22 Stat Attitudes
Affect Pre
Post 28.22
26.34 26.85
26.63 Competence
Pre
Post 32.30
29.80 30.24
29.36 Value
Pre
Post 43
41.72 43.27
40.03 Difficulty
Pre
Post 29.88
28.2 29.07
28.32 Cultural Sensitivity
Pre
Post 77
99.68 72.71
94.14 Note (*) denotes p < .05.
Promoting Active Learning through a Flipped Course Design
DISCUSSION
Results from the psychology statistics course study suggest the flipped classroom structure significantly improved learning, but no differ-ences were found between groups regarding attitudes toward statistics. Similarly, the flipped course showed a greater increase in intercultural sensitivity over the course of the semester, but after controlling for pretest scores was no longer significant. There were no significant differ-ences between courses in regards to changes in attitudes toward statistics. However, this is not surprising. Previous studies have found small, if any, differences between pre and posttest scores (Schau, 1999). Schau suggests these findings may be due to students’ overconfidence in their abilities to perform statistics at the beginning of the semester and/or their misunderstandings of what statistics can do for them. Interesting demographic differences were found regarding year in school that supports this claim.
At the beginning of the semester, it appears that first year students held the majority of posi-tive attitudes. First year students held significantly more positive attitudes toward statistics than fourth year students. First and third year students also believed they had more cognitive competence, or statistical knowledge and skills, than fourth year students. In addition, first and second year students thought statistics were less difficult than fourth year students. However, by the end of the semester, the differences by years decreased so that only third year students had more positive at-titudes toward statistics and believed more in their statistical knowledge than second year students.
Looking at overall trends, it appears as though first year students began the semester feeling con-fident and positive about statistics in comparison to fourth year students. However, this appears to flip by the end of the semester. Examining mean changes by year, first and second year students’
attitudes toward statistics become negative over the course of the semester, whereas third and fourth Table 3. Mean scores on pretest and posttest measures for each year in school
First Year Note (*) denotes p < .05. Significant differences between groups are marked by matching subscripts.
Promoting Active Learning through a Flipped Course Design
year students’ attitudes became more positive. It could be that first year students who feel confident about their statistical knowledge are more likely to take the course early in their college career, versus those who put off taking statistics possibly due to their lack in confidence. In addition, over the course of the semester, those who overestimated their skills and knowledge come to find that sta-tistics is harder than they thought, whereas those who lacked faith came to find how they had more skills and knowledge than they thought.
It is also important to discuss the additional learning opportunities the flipped course struc-ture offered over the traditional course, without sacrificing course content (Lage et al., 2000).
Common themes of these opportunities revolve around flexibility and students taking control of their learning. For example, as long as students maintained a minimum course grade, face-to-face workshop classes were optional. Brothen and Wambach (2007) also allowed students to do certain assignments online (vs. in class) as long as they maintained an acceptable grade. However, a number of students still chose to do work in class even though they had permission. We found similar results, with many students of varying talent still attending the workshops to complete their assignments. Some students likely needed the structure whereas others might have preferred having the instructor readily available in the event they needed assistance. It was also a time where students could work together and receive addi-tional support, which are opportunities students reportedly appreciate (Groves & O’Donoghue, 2009; Strayer, 2012). We also created an informal online discussion area meant only for students for those who did not attend workshops and/or those working after class. Similarly, Heinze and Procter (2006) implemented a “Virtual Café” where stu-dents could have informal discussions online in an attempt to foster a sense of community.
The flipped structure also allows for greater flexibility in what is covered and how. For ex-ample, having the lectures online allowed for other
face-to-face meetings to be used to apply statistics to diversity related research topics through read-ings, demonstrations, and guest speakers. Senn (2008) recommends using class time for hands on demonstrations or for examples in which students need to be shown step-by-step. Furthermore, these additional learning opportunities better prepared students to complete their own diversity related research project, which they picked as long as they met the course criteria. Giving students this control has been found to increase the variety of topics covered, examples used, and class discussions (Dengler, 2008). Similar to our experiences, Stacey and Gerbic (2007) found that students recognized the benefits of blending online and face-to-face formatting and employed the course elements that best addressed their needs. Specifically, students who were grouped together for a course project scheduled times to meet in person as well as shared important project documents online. This same collaboration has not been found in comparison to traditionally formatted classes (Strayer, 2012).
Application to Other Courses and Fields
The psychology statistics course described above is an example of a flipped classroom that utilizes blended learning though Internet technology.
We suggest that any college level course could be flipped in a very similar way. Lectures can be assigned as homework, streamed online or as downloadable files. As was done in the statistics class, professors could video-record staged lec-tures created especially for the course. Another option is to record live-lectures that took place within real classes during a previous semester.
These real, but recorded lectures, could then be posted online, or for students who have limited access to the Internet, the professor could provide the needed files to the students on a compact disk or a jump drive (Foertsch et al., 2002). Other options for lectures exist such as podcasts (audio recording only) or PowerPoint slides with voice
Promoting Active Learning through a Flipped Course Design
over. Such lectures can be made on a PC using the Acrobat Pro program or on a Macintosh using the iMovie application (Lage et al., 2000).
To better understand how the flipped classroom might look in various academic domains, consider the following examples. In a science class, such as biology, chemistry or anatomy, students could view PowerPoint files with voice over prior to coming to class. Class time could then be used in a more traditional science lab situation. Stu-dents would have twice as much time to work on experiments or worksheets as they would in a traditional course. Or, consider a course taught in an art or design department. Students could view pre-recorded lectures of professors demonstrating artistic, skillful, and difficult techniques. Students would be able to study and re-watch the videos so that when they come into the classroom they are able to immediately practice the new skill. Time spent working on the projects would be increased.
In this case, the professors are truly modeling skills for their students, who can learn through the observation and in-class practice.
In the above examples students are able to spend class time conducting experiments, working in groups, or individually on their own projects.
Self-directed study could also be used during class time (Lage et al., 2000). If one chooses to spend class time in this way, we would suggest that interactions between the faculty and student should still be cultivated and remain a focus of the time spent together. Foertsch and colleagues (2002) argue that being able to ask questions, and receive timely answers is a key feature of a flipped classroom. Students often do not know they have questions until they are actively working on the material. This is when they first become aware that they have a misunderstanding. When work is being done in class (instead of at home), students will be able to generate questions and interact with the professor to get the answers they need. Asking questions and receiving immediate feedback should lead to a better understanding of the course material (Foertsch et al., 2002).
Class time can be spent in additional ways then those already described. For example, reading prior to coming to class is an important aspect of many college courses. Professors struggle to get their students to consistently read. The flipped classroom could help in this problem. In-class time could be used to quiz students or give them other low-stakes assessments. Use of such quizzing is thought to increases students reading at home.
Studies have also found that repetitive quizzing of course material increases retention of that material later on, a phenomenon referred to as the testing effect (McDaniel, Anderson, Derbish,
& Morrisette, 2007). If quizzing is not a desired method, professors could have students generate questions for review that the class spends time covering together.
Although most of the examples of flipped classes in the literature have been small we en-courage professors to extend such pedagogy to courses with a larger numbers of students. Lage and colleagues (2000) suggest that their flipped economics course could be done with large class size, but that professors might break students up into smaller recitation sections. If recitation sec-tions are not possible, professors could employ teaching assistants and implement random col-lection and grading of work. For example, if a course runs 16 weeks, and students work in class to complete weekly-assigned worksheets (problem based learning), a total of six assignments could be collected and graded. The collection times would be random and unannounced during the semester.
CONCLUSION
Foertsch and colleagues (2002) asked what could face-to-face classes be used for if they were not used for lecturing? They note lectures are most effective when used as another source of informa-tion, much like a textbook. In this sense, lectures can be viewed outside of class and “face-to-face class time may then be used for more
pedagogi-Promoting Active Learning through a Flipped Course Design
cally powerful interactive exercises” (p. 273).
Similarly Cole and Kritzer (2009) note the flipped classroom provides, “a more efficient use of instructional time” (p. 38). Students work on gaining foundational knowledge on their own time so that class time can be used for deeper learning through application of the material they learned.
Similarly, many students mark the success of a learning environment through opportunities in the course to apply what they have learned (Strayer, 2012). The research presented in this chapter suggests there are a number of additional learn-ing opportunities that a flipped course structure offers over the traditional format. In the current study, both courses had the same homework as-signments, tests, and textbook but the flipped course allowed for additional readings to apply the material, application days, and a final project.
However, it is important to note that the flipped course structure might not fit every course, instruc-tor, or student (Beck & Ferdig, 2008; Osguthorpe
& Graham, 2003; Strayer, 2012). As mentioned previously, faculty need to determine which blend of best practices is best suited to meeting the learn-ing needs of students (Groves & O’Donoghue, 2009; Heinze & Procter, 2006). However, faculty might be hesitant to transition to a blended format for a number of reasons. Foertsch and colleagues (2002) note the increased time commitment and challenges to flipping a course, but believe teaching such a course is more fun because it al-lows faculty to better interact with students and facilitate learning. Flipped courses may be front loaded in terms of preparation, but this allows for more time throughout the rest of the semester to prep for in-class activities, tweaking the course, as well as decreases the amount of time needed for future courses (Cole & Kritzer, 2009). Faculty might also be concerned about whether students will view lectures if put online. However, the majority of students report watching most of the
& Graham, 2003; Strayer, 2012). As mentioned previously, faculty need to determine which blend of best practices is best suited to meeting the learn-ing needs of students (Groves & O’Donoghue, 2009; Heinze & Procter, 2006). However, faculty might be hesitant to transition to a blended format for a number of reasons. Foertsch and colleagues (2002) note the increased time commitment and challenges to flipping a course, but believe teaching such a course is more fun because it al-lows faculty to better interact with students and facilitate learning. Flipped courses may be front loaded in terms of preparation, but this allows for more time throughout the rest of the semester to prep for in-class activities, tweaking the course, as well as decreases the amount of time needed for future courses (Cole & Kritzer, 2009). Faculty might also be concerned about whether students will view lectures if put online. However, the majority of students report watching most of the