Classrooms of the Future2007 Everson

Teaching Statistics in the Online Environment : 

Teaching Statistics in the Online Environment Michelle Everson, Ph.D. Department of Educational Psychology University of Minnesota gaddy001@umn.edu

Overview: 

Overview Course development and structure Focus on active learning/conceptual understanding of course material Description of student assignments and assessments What do students think about the course? Some lessons learned Future directions

Slide3: 

“I really like the online format and I appreciate the individual attention that I receive from the TA and instructor. It's a little funny that an online course feels more personal than an actual in-person lecture.” “The instructor for this course has made me feel comfortable if/when I have any questions/concerns, and has fostered a true learning environment in which the ultimate goal is understanding the content.” (Comments from EPSY 5261 students)

The GAISE Recommendations: 

The GAISE Recommendations According to the Guidelines for Assessment and Instruction in Statistics Education (GAISE, 2005), introductory statistics courses at the college level should: Emphasize statistical literacy and develop statistical thinking Use real data Stress conceptual understanding Foster active learning Use technology Integrate assessments that are aligned with course goals Source: http://www.amstat.org/education/gaise/

Research on Teaching Statistics Online: 

Research on Teaching Statistics Online How can collaborative activities and technology can be integrated into an online statistics course? Student-to-student interaction and collaboration Weekly chats (e.g., Dereshiwsky, 1998) Project work (e.g., Davis & Chao, 2004; Prater & MacNeil, 2002; Suanpang, Petocz, & Kalceff, 2004) Regular group discussions (e.g., Grandzol, 2004; Jones, 2003; Tudor, 2006) Technology Courses have used Excel, SPSS, Minitab, Cyberstats, and ActivStats (e.g., Davis & Chao, 2004; Dutton & Dutton, 2005; Grandzol, 2004; Harrington, 1999; Lawrence & Singhania, 2004; Mills & Xu, 2005; Prater & MacNeil, 2002; Tudor, 2006; Utts et al., 2003; Zhang, 2004)

Introductory Statistical Methods (EPSY 5261): 

Introductory Statistical Methods (EPSY 5261) This is a 3-credit, semester-long, graduate-level introductory course taught through WebCT Prerequisite is high-school algebra Students in the course come from a variety of different areas College of Education School of Nursing Other programs: Journalism, Speech Communication, Business, etc. Students take the course for a variety of reasons Some plan to go on to other courses Some will not need to take any other statistics courses Many select the online course because of convenience

Assignments and Assessments: 

Assignments and Assessments Grades are based on: Small-group Discussion Assignments (8) Homework Assignments (4) Critique of an Academic Journal Article (1) Quizzes (3) Project (1) Final Exam (1) Students also have the opportunity to complete non-graded practice activities and extra credit assignments

Collaborative Discussion Assignments: 

Collaborative Discussion Assignments Each student is assigned to a discussion group at the beginning of the semester Eight small-group discussion assignments are completed Assignments involve discussing concepts and answering questions as a group Students must post their own thoughts AND respond in a meaningful way to what at least one group member has posted One student volunteers to lead each discussion and submit a summary to the instructor by midnight on Monday

Assignment #1: Designing the Perfect Experiment: 

Assignment #1: Designing the Perfect Experiment Students are told the story of Scott Ginsberg (see the website www.hellomynameisscott.com) Students discuss how they might design an experiment to determine if wearing a name tag causes others to be more friendly (or causes a person to become more approachable) Through discussion, students talk about issues such as sampling, bias, control, and other experimental design issues

Assignment #4: Sampling Distributions: 

Assignment #4: Sampling Distributions Students work independently through a lab in which they use the Sampling SIM program (delMas, 2001) Students then attempt to answer a series of questions about the lab as a group: They talk about what they feel a sampling distribution is and why it is important. They talk about why they think the sampling distribution has the characteristics that it does. They work as a group to answer a question that involves applying knowledge of sampling distributions.

Assignment #7: Correlation and Regression: 

Assignment #7: Correlation and Regression Students talk about what variables might predict success in college, and how we might measure “success” After initial discussion, students are asked to examine a real data set that includes test scores, GPAs (high-school and college), and other data from several college students Students try to determine, based on the data set, how they might construct a regression equation to predict college GPA Through discussion, students talk about their understanding of both correlation and regression

Homework: 

Homework Students complete 4 homework assignments, each worth 10 points Assignments involve answering questions from the course textbook Most assignments involve using SPSS or other technology (e.g., Java applets) Assignments are submitted as Word attachments through WebCT e-mail The TA grades each assignment and sends individual feedback to the student within one week

Project: 

Project Each student completes a project that involves gathering data from two groups and describing/analyzing the data using SPSS The project is submitted in parts: Part 1: Project idea Part 2: Project data Part 3: Introduction and description of data Part 4: Inference (confidence intervals and hypothesis testing) and summary/conclusion

Exams: 

Exams Quizzes are administered (roughly every 4 weeks) online through the WebCT quiz tool Available from noon on Fridays until noon on Mondays Students have up to three hours to complete the quiz (in one sitting) Quizzes consist almost entirely of short-answer questions Students complete a “take-home” final exam The final is a project that involves answering questions about a data set using SPSS The BIG question: How do you administer quizzes online and ensure that students are not cheating? Can you do this????

Preventing Academic Dishonesty in the Online Environment: 

Preventing Academic Dishonesty in the Online Environment If all (or most) of your quizzes will be online, you can do different things to prevent academic dishonesty Change assessments from semester to semester Insist that students complete the quiz in one sitting, within a certain period of time Use open-ended questions where students must explain their answers You can also randomize the order in which questions are presented to each student Ask that students adhere to an “honor code” of some kind

Student Feedback: 

Student Feedback In midterm feedback surveys, students were asked to indicate how strongly they agreed that certain components of the course contributed to their understanding of statistics Data from the last three semesters of EPSY 5261 were pooled Overall, student feedback (both at midterm and at the end of the semester) has been relatively positive

More Student Feedback: 

More Student Feedback

Student Performance: 

Student Performance Students who take this course tend to be highly motivated, and most do well (the typical course grade is an A) Although we have not systematically compared performance in this online course to a traditional face-to-face course, we have noticed that students tend to do about the same regardless of the format of the course Certain online students, however, might benefit more from a traditional setting

Lessons Learned: 

Lessons Learned Teaching online can be a big time commitment Online courses are NOT for everyone! You get to know your students in a much different way when teaching online Students appreciate timely communication with the instructor/TA, organization, and consistent deadlines Online discussion assignments can be a great way to learn more about student difficulties/misconceptions They motivate ALL students to participate Discussions can be monitored for ALL GROUPS from start to finish Set deadlines discourage students from waiting until the last minute to participate

Future Directions: 

Future Directions In the future, we hope to spend time: Developing software tutorials to help students learn to use SPSS Comparing the online course to a face-to-face counterpart Learning more about how students think and reason about statistics by looking carefully at the quality of discussions Determining how to better motivate students (especially undergraduates) to participate more actively in the online course

Slide26: 

Thank you!!!