Course Redesign ePortfolio Showcase

STAT 108 is converted and compressed into an intense eight week fully-online course. Besides the pedagogical aspects inherent in an online course, the online delivery provides scheduling flexibility to students and frees infrastructure resources for the university. The eight week compression of the course keeps the students "in-the-zone" and avoids the fatigue that can result near the end of a 15 week semester course.

This project aims to integrate MOOC and other open-source materials into Canvas, the LMS used at SJSU. Previous versions of this course required students to visit multiple web sites to access course materials and activities. Students expressed frustration and confusion at having to keep track of content and activities across these web sites. This dissatisfaction might have had a detrimental effect on student learning outcomes and engagement. In addition, the use of multiple web sites makes course-related activities more effortful and adds a substantial time barrier for students. One purpose of the project is to reduce the number of web sites students must visit to access course materials and activities. Another purpose of the project is to examine ways to improve student engagement, self-regulation, and self-reflection (e.g., through self-monitoring, goal setting).

Stat 250 is a general elective introductory statistics and data analysis course for students throughout the sciences, social sciences, health and human services, and business. This course redesign develops a flipped classroom format whereby students learn core statistical concepts in online videos created by the instructors and participate in computer data analysis labs and directed problem-solving discussions. The aim of this approach is to teach statistics by doing, internalizing key concepts in experimental design, data collection, and analysis as well as statistical communication and assessments through an active classroom learning environment. The ultimate goal is to scale this effort up to all introductory statistics courses taught on campus, through online core concept lectures and subject-specific data analysis/statistical problem solving laboratories.

Biometrics (BIOL 300) was redesigned by replacing the weekly face-to-face laboratory sessions, which are held in a computer classroom, with online labs. Virtual lab activities were developed and integrated into the assignments so that students were involved in both data collection and data analysis. The lecture remained face-to-face. This mode of delivery decreased the cost per student by 55% and allowed more sections of the course to be offered. Pre- and post-surveys were administered to sections using traditional labs and sections using virtual labs. Analyses of the survey responses and course grades showed that there were no significant differences between the two delivery modes in the students increase in knowledge about statistics or in their attitudes towards statistics. These results suggest that the biostatistics virtual labs are just as effective pedagogically as the traditional labs, but more cost efficient.

In this project, we consider redesigning the curricular foundations of the introductory statistics course at Cal State Fullerton. This is mainly approached through producing short videos that highlight the major themes of the class. Moreover, we aim to revisit the pedagogical aspects of the intro course in larger classroom settings, through utilization of audio-visual tools, as well as incorporation of R, the most popular statistical programming language. This course redesign will also provide training opportunities for the introductory statistics faculty.

This course is a Psychology major upper division core course. All Psychology students are required to take this course. In general, Psychology students are not excited to take this course and find statistics extremely difficult. The vast majority of students do not have calculus experience. Many of these students are not confident that statistics will be useful in their desired career. One hypothesis is that undergraduate students view statistics largely as a set of disparate quantitative formulas. Perhaps the solution is to teach statistics in a way that emphasizes a coherent understanding of introductory statistical concepts.

Stat 250 is a general elective introductory statistics and data analysis course for students throughout the sciences, social sciences, health and human services, and business. This course redesign develops a flipped classroom format whereby students learn core statistical concepts in online videos created by the instructors and participate in computer data analysis labs and directed problem-solving discussions. The aim of this approach is to teach statistics by doing, internalizing key concepts in experimental design, data collection, and analysis as well as statistical communication and assessments through an active classroom learning environment. The ultimate goal is to scale this effort up to all introductory statistics courses taught on campus, through online core concept lectures and subject-specific data analysis/statistical problem solving laboratories.

Stat 350 is a core course for statistics, computer science, and other quantitatively orientated majors in Science, Technology, Engineering and Mathematics (STEM) disciplines.The demand for the class has grown rapidly in recent years, from a total of 41 students in the year of 2010 (offered only in the Fall) to a total of 175 students in 2015 (52 in Summer 2015 and 121 in Fall 2015). We develop a hybrid/flipped model of instruction during Fall 2015 to tackle three difficult areas in the course: available seats, DFW rates, and training in statistical computing for a large enrollment class.

Stat 250 is a general elective introductory statistics and data analysis course for students throughout the sciences, social sciences, health and human services, and business. This project entails the second phase of the course redesign. In the first phase, statistical computing lab assignments (simulations and data analyses), concept review and computing demonstration videos, and LMS-based conceptual online homework assignments were developed. These aspects were incorporated in the Spring 2015 offering of the course, each offered online as part of the students' work outside the classroom (ePortfolio: http://contentbuilder.merlot.org/toolkit/users/sdsumathstat/sdsu_stat250_course_redesign.) In this second phase, we will develop a flipped classroom format whereby students learn core statistical concepts in online videos created by the instructors and participate in computer data analysis labs and directed problem-solving discussions in the classroom. The aim of this approach is to teach statistics by doing, internalizing key concepts in experimental design, data collection, and analysis as well as statistical communication and assessments through an active classroom learning environment. The ultimate goal is to scale this effort up to all introductory statistics courses taught on campus, through online core concept lectures and subject-specific data analysis/statistical problem solving laboratories.

The proposed redesign was to "flip" the class and move some of the lecture on-line for students to watch before class. This would free up more class time for students to complete in-depth activities, interact more with the material, each other, and the instructor. The goal was to produce new in-class and out-of-class exercises that truly engage the students in the course material at a level that improves their retention because they understand the nuances and logic behind the many choices one makes in conducting appropriate statistical analyses, rather than just memorizing definitions or steps. The primary goal has been increased retention of key concepts leading to lower DFW rates in both SOC 101 and 102 (the Research Methods course that follows).

This is an introductory statistics class which covers the traditional introductory topics and uses StatCrunch as the statistical software package.

Project Abstract: This project entails creating virtual labs for the online portion of Math 105.

The course is a prerequisite for many upper-division courses and currently has a high failure rate of about 23% across sections. The course redesign is intended to increase student success by incorporating video tutorials and adaptive assessment to facilitate learning and reduce lecture time in class and create more time for active learning and problem-solving sessions. A course project will be used to give students a comprehensive experience in using statistics in scientific research. Supplemental instruction and tutoring services will be offered to provide an extra learning opportunity and practice for students.

The redesigned course will involve a flipped format in which students will watch videos demonstrating the course content outside of the class and will spend time during class working on activities. The readings and videos will be available to the students for free from a combination of sources. Links to videos and readings will be accessed via the Moodle Learning Management System.

This class is required by Psychology majors and students must complete the class with a "C-" or better. However, many Psychology students do not expect to take a statistical class, and may feel under-prepared for the mathematical component. By adopting a flipped model of instruction, students can be aware of the concepts prior to class, spend the time in-class practicing the application, and then utilize supplemental instructional material outside class to clarify any points that are muddy. This should lead to deeper learning and retention which will impact success in this class as well as in the next class in the methods sequence.

Many students are underprepared when enrolling in statistics and independent learning. The goal of the redesign is to improve the student learning experience by creating instructional videos that will guide them and make this experience more similar to a face to face class. Instructional materials will be developed to help students stay on track and learn the material. Students should have a clear understanding of what the learning objectives are and how to accomplish them. The course will be redesigned around modules for enhanced learning.

MTH 107 is an elementary statistics course that has traditionally had a high DFW rate (in the 30-40% range), in part due to poor mathematical preparation for the student body required to take this course (International Business and Global Studies majors) and the nature of how statistics is often taught. In our increasingly data-driven world and with the rise of big data, statistics courses must take on a more computational emphasis that enables students to work with real world data. Our aim is to improve student outcomes in their quantitative skills while also empowering students to use statistical methods to solve real world problems. To accomplish this, we propose to focus on application-driven projects and analysis using both Excel and RStudio.

Our course redesign project spans three courses and four redesign interventions: The use of analytics, instructional videos and interactive applets, peer tutors, and input from client disciplines to make these lower division "introductory" courses appear more applicable to students and thereby increase their interest, participation, and ultimately, passing rates.