Overview

Course Description

This graduate course covers a variety of research methods & statistics commonly applied in the Learning Sciences and related fields. You will learn when and how to apply methods relevant to assessment that are applicable in both laboratory and field settings. Methods covered include basic and non-parametric models, regression analysis (linear & logistic), moderation, mediation, statistical equation modeling (SEM), univariate and multivariate analysis of variance, repeated measure & mixed design analysis, factor analysis and data reduction techniques, and multilevel hierarchical models. These methods will be applied using IBM SPSS Statistics, a powerful software package commonly used in the social sciences and well known for its graphical user interface and point-and-click execution. You will gain a working knowledge of this software and the aforementioned analytic methods through a series of hands-on assignments and through completion of a course-long project utilizing data of your choice. This project will require that you formulate research questions, define a hypothesis, utilize research designs that will test your predictions, collect and analyze data, and report your findings in a well-developed journal article or conference submission. Professional skill development will also include the critical analysis and communication of published work in your field. There are no formal prerequisites for this course, but experience with statistics at the level of regression analysis may be a helpful precursor. In addition, previous experience with SPSS will be helpful in tackling assignments and project work, but support will be provided to novices.

Course Objectives

Upon completion of this course, I anticipate that you will...

1. Gain a working understanding of when and how to use common univariate and multivariate research methods & statistics applied in the learning sciences and related fields.
2. Gain a working understanding of SPSS, how to interpret SPSS output, and how to translate SPSS output into coherent results presented using APA format.
3. Gain experience processing, analyzing, and drawing conclusions from large datasets and communicating your findings effectively in pursuit of peer-reviewed journal or conference publications in your area of interest.
4. Gain confidence in digesting statistical content and think critically about how other scholars have used statistical methods to analyze and interpret their data.
5. Develop solutions for difficult problems, expand your critical thinking to new situations, and broaden your perspective within your field.

Teaching Philosophy

My teaching philosophy stems from my education, from the teachers and professors that forged a path for me, and from my experiences with teaching and advising. I recently completed my dissertation on the evolution and application of educational research at scale within the ASSISTments online learning platform in the Learning Sciences & Technologies program here at WPI. The application portion of my work called upon a wealth of literature in psychology and cognitive development, with specific regard to student motivation and learning. In pursuit of my degree, I developed a series of randomized controlled trials assessing the efficacy of learning interventions targeting autonomy, belonging, and competence. These elements, thought to be innate needs, are the primary tenets of Self-Determination Theory. In need-supportive environments, learners are more likely to display self-determination, intrinsic motivation, and ultimately, academic achievement. My teaching philosophy targets the fulfillment of these needs.

As an adult enrolled in a graduate program, I trust that you are a self-determined learner, simply seeking a safe environment to learn and practice the skills necessary for your future as an academic or industry professional. As such, I will strive to create a learning environment that fosters autonomy through project-based assignments with a personal emphasis. Throughout the semester, you will craft a publication-worthy journal or conference paper on a topic of your choice, using a dataset of your choice, and featuring a selection of the analytic methods covered in class. I hope that this project offers flexibility and shows my respect for your research focus, contextualizing your learning to optimize your personal development.

Understanding the value of connecting with others, I will also work to foster belonging in the classroom by promoting a strong community of support. Learning environments should encourage risk-taking and focus on strengthening communication and leadership skills to promote long-term success. During the semester, you will be expected to facilitate one class discussion of a pre-selected analytic method. The presentation format requires that you critique a publication from your field that features the methodology, before implementing the method with your own dataset and walking your peers through an interpretation of your results. I hope that this task leaves you feeling especially confident in the method that you chose while inspiring higher order thinking and a sense of community among your classmates.

My time as a graduate student at WPI also taught me the value of competence as I learned to tackle large projects through smaller, iterative achievements. The project-based environment also solidified that long-term retention is not generated by testing, but instead by personal application. A sense of competence, or feeling capable in the task at hand, is a fleeting ideal as one progresses through higher education; as more is learned, the vast unknown is realized, leaving learners feeling small and sometimes, like “imposters.” As such, it is critical to foster a sense of competence in the classroom by creating challenging yet attainable goals that are supported by robust feedback. A series of method understanding assignments will be used to promote competence through familiarity, challenge, and support. I hope that this process promotes higher order thinking while supporting the accumulation of discipline-specific knowledge.

Although this will be my first graduate class on the other side of the podium, I have taught and advised in various capacities throughout my life, and I have a decade of experience working with most of the material we will cover in class. I cannot promise that I will be able to answer all questions on the spot, but I can promise that I have compiled a multitude of resources that will help us learn together. I can also promise that I will not take myself too seriously and that I will strive to nurture growth in each of you as individuals as well as in the collective community. I suspect that my teaching philosophy will evolve as I grow alongside you this semester, and I welcome your feedback.