Computer Science Professor Awarded NSF Grant

The National Science Foundation has awarded Jason Hemann, Ph.D., a substantial Research and Development grant for his project, “Systematic Construction of Teaching Language Progressions for Embedded Domain-Specific Languages.” The goal of this project is to create a software program designed to teach those who are more inexperienced to learn programming languages. Traditionally, the software programs that already exist are designed with experts in mind. But Hemann’s program, “Racket,” is designed to take someone from a novice level of learning through the advanced stages of programming. Hemann has been conducting this research for 10 years, but this highly-competitive NSF grant will provide Hemann with the necessary time and resources needed to achieve this goal over the next two years.

Because the “Racket Programming Language” is designed with inexperienced students in mind, those learning how to program are instructed on a “scaffolding” or tiered system. Students are taught foundational building blocks needed for programming and can only progress towards the next stage of programming after they have mastered the previous one. The Racket Programming Language is also equipped with software to recognize where a student can use further support in their learning. Using algebraic pattern matching, Hemann can inspect and extract the data from the data configurations. Hemann has adopted algebraic pattern matching for Racket from programs like Java, JavaScript, and Python, where it is commonly used.

In preparation for designing Racket, Hemann had to research various levels of programming skills among non-computer science students, computer science majors, and professional programmers. As a result of this work, Hemann has authored numerous papers, along with a textbook to aid in the development of programming language education. As his research continues to evolve, Hemann plans to design, implement and evaluate the teaching levels of variants of Embedded Domain Languages.

Though the research and its findings have been an exciting process, Hemann says that the most rewarding part of this process has been “collaborating with students that have more recently learned to program.” The idea of the project, Hemann explains, is to develop languages to help people learn to program, so students make perfect collaborators, as they more readily identify as new programmers learning to program and therefore provide an invaluable perspective as learners. "Students make good authors and co-editors," Hemann added, "and many students in Computer Science as in other STEM programs at Seton Hall collaborate with faculty on publications."

Seton Hall offers a robust BS as well as Minors in Computer Science and in Data Visualization and Analysis, and a Certificate in Cybersecurity, which can add a versatile, in-demand skillset to any other A&S major. Seton Hall also offers a dynamic MS in Data Science, which empowers graduates with data analytics and engineering skills, including machine learning, to manage big data and decision-making in various fields, from business to STEM. Students with interest in Computer Science who would like to learn more about Hemann’s research or join his research group can contact Professor Hemann ([email protected]).

Categories: Research, Science and Technology