Teaching

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Teaching Awards and Recognition

During my tenure at Gordon Ford College of Business, I have diligently adhered to its rigorous teaching standards. My efforts have been acknowledged by various individuals and entities within the university. The accolades enumerated below underscore the recognition I have received for sustained excellence in Teaching Effectiveness.

• In 2022, I was awarded the College Faculty Award for Excellence in Teaching.
• In 2022, I received the MBA College Innovative Pedagogy Award, a testament to my dedication to introducing and applying innovative teaching methodologies, thus improving the educational experience for my students.

Teaching Statement 

In my academic journey, I am guided by a pedagogical philosophy deeply anchored in the conviction that active participation, both within and beyond conventional classroom boundaries, forges enduring and transformative connections between educators and learners. 

This commitment not only amplifies my professional satisfaction but also fosters innovation and bolsters our faculty's cumulative input to the dynamic landscape of modern education. Consistent with this philosophy, I have designed my teaching approach around three pivotal dimensions:

1. Relevance Through Application: I engage students with actual business dilemmas, ensuring their mastery in data modeling surpasses theoretical understanding, resulting in practical and implementable solutions.
2. Bridging the Academic Gap: Through initiatives like the poster competition, I aim to motivate students to consider higher academic endeavors, perhaps even progressing to a master's program.
3. Inculcating Research Philosophy: I maintain an active collaboration with students keen on an academic research pathway. They are mentored to showcase their insights at professional conferences on regional, national, and global platforms.

Teaching Strategies

In my pursuit of teaching excellence, I closely align my teaching methodologies with four principles outlined in "How Learning Works—7 Research-Based Principles for Smart Teaching" by Ambrose et al. (2010):

1. Promoting Self-Directed Learning: I actively foster students' self-monitoring and self-generation abilities. My approach is hands-on: guiding each student in formulating business research questions, nurturing their professional writing abilities, and imparting skills to conduct sound business-based research.
2. Fostering Collaborative Classroom Dynamics: I aim to craft a learning environment where students are inspired to both collaborate and apply their newfound knowledge meaningfully in their lives. Recognizing the diverse learning preferences of students, as noted by Coffield et al. (2004), I employ a range of pedagogical models, including flipped classroom (Roehl et al., 2013); metacognitive strategies; TARGT framework for motivation (Morrone & Pintrich, 2006), in contrast to the DMGT framework that emphasizes intrinsic motivation (Gagné et al., 2010); and activities incorporating Mayer-Salovey-Caruso Emotional and Social Intelligence Test (Mayer et al., 2002).
3. Understanding Students' Motivational Drivers: At the heart of my teaching philosophy lies the commitment to help students grasp the foundational principles of business data analytics, connecting them with real-world applications. My threefold approach is:
   • • Contextualizing core principles through practical examples
     • Showcasing the overarching narrative of their field by interlinking course concepts
     • Cultivating their critical thinking abilities, as advocated by Snyder & Snyder (2008).
4. Optimizing Learning through Constructive Feedback: My courses often feature both individual and group projects, with the complexity determining their timeline. By employing a scaffolding approach, I ensure students progressively grapple with intricate tasks. My office hours are dedicated to concept clarification and discussion, supplemented with quizzes to assess their grasp. I believe in a dynamic, interactive teaching style, enhanced by varied techniques that simplify students' learning trajectories. Additionally, I emphasize the importance of hands-on experience in data analytics and the art of effective communication, often facilitating classroom presentations and poster sessions.

Curriculum Development: Implemented New Courses

During my tenure at the Gordon Ford College of Business since August 15, 2013, I have participated in the design and refinement of the department’s curriculum. Specifically, I have been involved in the design of seven distinct courses within the Computer Information Technology and the Business Data Analytics Programs. Throughout this period, I have instructed six distinct courses and took the lead in curriculum development for five of them. Among these courses, one is designed for the master's level, namely “Contemporary Analytics.”

For a detailed list of courses, I have developed, please refer to the following:

• • Contemporary Analytics (BA/BDAN 513)
  • Data Mining/Predictive Modeling (BDAN 420)
  • Data Visualization (BDAN 430)
  • Business Data Analytics (BDAN 310)
  • Knowledge Management (CIT 486)

Furthermore, in the development of the core course, Introduction to Analytics (BDAN 250), I contributed to the foundational design by incorporating elements from the Tableau Data Visualization Literacy Curriculum into a structured Blackboard course format. 

Initiatives

Since 2014, I have served as a representative of GFCB on the University Student Research Council. I also actively participated in the University Graduate Council's Research Subcommittee from Fall 2016 to Spring 2019 and subsequently from Fall 2020 to Spring 2023. Through these roles, I've gained insights into diverse student research trajectories, which have informed the development of tailored opportunities for GFCB students. 

To further foster research-driven education, I've revamped both upper-division undergraduate courses and master’s-level programs, integrating comprehensive research projects. These enhancements have been instrumental in enriching the academic experiences of students majoring in marketing, economics, finance, accounting, business data analytics, management, and health informatics.

The "Predictive Modeling" course, formerly "Data Mining," imparts foundational knowledge in data mining and predictive analytics to business data analytics majors. The structure of this course emphasizes hands-on, project-based learning. Instead of traditional final exams, the curriculum includes a Capstone Project, providing students an opportunity to apply strategic business reasoning, communication skills, and consultative approaches. 

Through the course, students engage with business cases from various industries, highlighting the strategic importance of analytics. They receive a thematic guide for strategy development, and dual-major students have the flexibility to select projects aligned with their primary academic focus.

This course teaches business data analytics majors the fundamentals of data mining and predictive analytics. It is a practical, project-based course. Instead of the final exam, students work on a Capstone Project. This project is the culmination of the business data analytics program, and it provides students with the opportunity to demonstrate their strategic business thinking, communication, and consulting skills. 

• These business cases are across various industries, and application areas illustrate the strategic advantages of analytics. Students are assigned to a specific theme to generate business and project execution plans. Dual-major students can choose Capstone Projects closely related to their first major with an analytics modeling focus. 

• While the Capstone theme falls under various domains such as business analytics, finance analytics, marketing analytics, health analytics, sports analytics, etc., students work individually on projects within their preferred analytics focus.  

At the end of the semester, students should be able to

• Critically identify which algorithms and methods better solve the final Capstone Project.
• Productively present a solution to analytical problems in the Business Analytics Posters Competition.

Before this Competition, I host workshops where students are advised on the Competition's rules and guidelines, what goes into a good research business plan, and how to prepare and pitch their ideas through formal presentations. She spends one-on-one time with each student after the presentation of materials. Accordingly, students can compete among their peers and those who desire to extend their research; she mentors them for another year through FUSE grants and, in some cases, might expand into two-to-three as a master’s thesis. 

Selected students were given a chance to present at various conferences and participate in state, national, and international conferences such as the Teradata Analytics Universe and INFORMS.