City Tech’s CUNY 2x Tech program will support nearly 2,000 students from the Computer Systems Technology department majoring in Computer Information Systems, Computer Systems Technology, and Data Science,” said Pamela Brown, provost and vice president, academic affairs, City Tech. “With a hands-on approach, these majors prepare students for careers in emerging information technologies, with applications in business, science, technology, and other fields. Career exploration and readiness will be integrated throughout the curriculum in all our majors, with the support of newly hired faculty and academic/career advisors with relevant industrial experience. We will also expand upon existing collaborations such as the NYC CEO Jobs Council apprenticeship program and utilize college resources such as tutoring, mentoring, and the Student Success and Professional Development Centers, to ensure academic success. Our Computer Systems Technology students reflect the rich tapestry of New York City, and we are proud of the contributions our graduates make to the diversity of the New York City workforce.
We are honored to receive a best paper award at the ASEE Mid-Atlantic Fall 2020 Conference for our paper entitled “Impact of Open Education Resources (OER) on Student Academic Performance and Retention Rates in Undergraduate Engineering Departments” with Yongchao Zhao and Cailean Cooney.
I am pleased to announce that the article titled: “Our Stories: First-year Learning Communities Students Reflections on the Transition to College”, is published in Learning Communities Research and Practice (LCRP). This article is co-authored by the FYLC (First Year Learning Community) researchers: Karen Goodlad, Jennifer Sears, Mery Diaz, Sandra Cheng and Philip Kreniske. The full article can be viewed at: https://academicworks.cuny.edu/ny_pubs/538/
Analysis of diverse first-year and first-generation learning communities students’ reflective narratives shows this population of students at an urban commuter college of technology face significant challenges in the transition into college. Designed to assist in this transition, the “Our Stories” digital writing project incorporates reflective writing in the long established, yet recently revitalized, learning communities program. Through analysis of the “Our Stories” project, we examine how the structure of our learning communities program, together with writing on an open digital platform, builds community and has the potential to positively influence students as they identify, and begin to make sense, of the social, emotional, and bureaucratic challenges in their transition into college. The role of peer mentors, faculty and administrators in this project is discussed.
I am pleased to announce that our paper titled: “Using Prescriptive Data Analytics to Reduce Grading Bias and Foster Student Success” is accepted for publication at the IEEE Frontiers in Education (FIE) conference 2019 to be held in October 16-19, 2019. This paper was co-authored by Reneta Lansiquot (City Tech) and Christine Rosalia (Hunter College). This is a seminal paper on the topic of reducing grading bias in the classroom by using data analytics. The abstract is as follows:
Abstract: This innovative practice work-in-progress paper presents our approach of using data analytics as an alternative solution to eliminate grading bias. Effective grading involves maintaining consistency among all students, irrespective of gender, race, ethnic background, and prior performance. Related work in this area has shown that prior work submitted by a student influences future scores given. Some of the popular methods used to eliminate grading bias involves grading rubrics, anonymous or blind grading, and/or computerized auto-graders. In spite of all these methods, some types of grading such as essays and projects still require subjective grading, which opens the door to conscious or unconscious bias.
Given the student data available regarding performance, colleges and universities are turning to analytic solutions to extract meaning from huge volumes of student data to help improve retention, graduation, and student performance rates. While looking at all the analytic options can be a daunting task, these analytic options can be categorized at a high level into three distinct types: (a) Descriptive Analytics, which use data aggregation and data mining to provide insight into the past and answer “What has happened?”; (b) Predictive Analytics, which use statistical models and forecasts techniques to understand the future and answer “What could happen?”; and (c) Prescriptive Analytics, which use optimization and simulation algorithms to advise on possible outcomes and answer “What should we do?” In this paper, we use Prescriptive Analytics to provide students with advice on what action to take, based on a tool which predicts each student’s performance.
I am pleased to announce that our paper titled: “Using Natural Language Processing Tools on Individual Stories from First Year Students to Summarize Emotions, Sentiments and Concerns of Transition from High School to College” was accepted and presented at ASEE National Conference held in Tampa, FL between June 15th-19th, 2019. It was a project in collaboration with First Year Learning Community leaders: Karen Goodlad, Jennifer Sears, Phil Kreniske, Mery Diaz and Sandra Cheng.
Abstract: Research indicates striking disparities in college completion rates between students who are first generation and come from low-income households (FLI) as compared to continuing generation students. At New York City College of Technology, CUNY (City Tech) the majority of the student body are FLI. In the last decade, educators have made great efforts to re-shape and improve students’ First-year college experience with a focus on FLI students. One of the ten high-impact educational practices recognized nationally to improve first year student persistence and retention is First-Year Learning Communities (LC). A LC is a group of students who enroll in two or more courses, generally in different disciplines that are linked together by a common theme, in an academic semester. LCs involve cooperative learning, alternative assessment in the classroom, cross-disciplinary writing assignments, and critical thinking activities. LCs first came to our institution, City Tech, through a Title V Grant in 2000 and were adopted by the college in 2005. The academic performance of students participating in LCs at City Tech reflects national trends. When compared to the general population at the College, students in LC earn higher GPAs, have higher retention rates, and demonstrate greater satisfaction.
In order to complement the community-building efforts within learning community classrooms, we, a cohort of faculty leaders and administrators of City Tech’s First Year Learning Communities, a program offered through the college’s Office of First Year Programs, developed “Our Stories” digital writing project which extends the student’s network beyond the physical and temporal limits of class meeting times. Students in our LC were given the opportunity to share their personal stories of the transition from high school to college on a digital platform called OpenLab, a campus-wide, open digital WordPress platform for teaching, learning, and sharing. Over the course of a semester, LC students were prompted with the same prompt three times, at the beginning of the semester, roughly in the middle of the term, and in the last weeks. Peer Mentors, upper level students who, among other responsibilities, were trained to respond to “Our Stories” posts actively engaged in the project.
We analyzed student stories, using text analytics tools such as Natural Language processing (NLP) and Tone Analyzer to better understand the transition experience. The NLP analyzer helped summarize emotions and concepts, and identified some common concerns of students by identifying common keywords. The Tone Analyzer tool uses linguistic analysis to detect joy, fear, sadness, anger, analytical, confident and tentative tones found in text. Such summarizations of student stories provide suggestions to the college on how we can better orient students and prepare them for their first year. In this paper, we present top concerns of students who are transitioning from high school to college. We will also investigate through the stories if the overall experience of students gets better or worse through their first year.
I am pleased to announce that I have been awarded the 2019-2020 Cycle 50 PSC-CUNY Research Award (Traditional A) for research in “Using Data Analytics for Personalization of Online Tutoring Systems” to begin July 1st 2019.
I will be presenting the following workshops during March and April 2019
- Scholarship Workshop on “Scholarship of Teaching and Learning” (Location: Academic Building 209, March 15th, 9 – 11:30am)
- Teaching Workshop on “Overcoming Apathy in the classroom”. The same workshop will be presented at the following dates and times. Please pick one that suits you. This workshop is open for full-time and part-time faculty:March 21st (Thursday) – 2:30pm – 3:30pm OR April 2nd (Tuesday) – 4:30pm – 5:30pm. Both workshops will be held at N-227.
- Assessment workshop on April 12th (Location TBD)
Hope to see you all at some or all of the workshops above.
I am pleased to announce that I have received the Teach Access Faculty Curriculum Development Grant award to advance the teaching of the design and development of accessible technologies.
About Teach Access: Teach Access is a unique collaboration among members of higher education, the technology industry and advocates for accessibility, with a shared goal of making technology broadly accessible by infusing fundamental concepts and skills of designing and developing accessible technology into higher education. Teach Access includes members from leading tech companies,academic institutions and disability advocacy organizations and other non-profit institutions. Teach Access operates as a fiscal sponsorship fund at the Silicon Valley Community Foundation (SVCF). To learn more visit teachaccess.org or email email@example.com .
I am pleased to inform that our Poster titled “A Peer based Tutoring and Mentoring Model for First Year Computer Science Courses Based on Strategies Used by Songbirds for Learning”, (with co-author L. Baron) has been accepted for publication at the 50th ACM Special Interest Group on Computer Science Education (SIGCSE ’19) to be held from February 27– March 2nd, 2019 at Minneapolis, Minnesota, USA.”
I will be giving talks (as part of panel discussions) at the following venues:
Third Annual City Tech Symposium on Science Fiction, Tuesday, Nov 27th, 2018. 4:00pm-4:50pm
Topic: Frankenstein Panel: Mary Shelley’s Novel’s Influence on Scientists and Technologists
Location: Academic Complex A105
Moderator: Justin Vazquez-Poritz
Heidi Boisvert, Entertainment Technology Department
Robert MacDougall, Social Sciences Department
Ashwin Satyanarayana, Computer Systems Technology Department
Jeremy Seto, Biological Sciences Department
17th Annual CUNY IT Conference (Nov 29-30th), 2:15pm – 3:15pmTopic: Mapping Brooklyn: Digital Tools to Support Place-Based Learning
Abstract: Participants from a range of disciplines will discuss their experiences using geospatial mapping tools for research on, and instruction in, Brooklyn’s social history and urban development. We will confront a central challenge in using technology in undergraduate education: developing digital tools that are at once approachable and compelling, while providing sophisticated computer-based applications that have the capacity to yield new insights into topics from the humanities.
Christopher Swift (Presider), Associate Professor of Theatre
Ting Chin, Assistant Professor of Architectural Technology
Anne Leonard, Associate Professor of Information Science
Anne Leonhardt, Associate Professor of Architectural Technology / Director of Digital Technology
Sean MacDonald, Professor of Economics
Ashwin Satyanarayana, Associate Professor of Computer Systems Technology
Satyanand Singh, Associate Professor of Mathematics
Peter Spellane, Professor of Chemistry
Venue:John Jay College of Criminal Justice (524 West 59th Street, New York, NY 10019)