P120A190062
Presentation of the design and development of a Data Science Post-Baccalaureate Certification Program at Inter American University of Puerto Rico, based on project learning, working in small groups and emphasis in analysis and communication of results. It has been developed through experimental workshops in summer, directed by experts with participation of faculty and students. We show examples of interactions in the workshops and students' presentations.
Jeff Milbourne
STEM Coordinator-Writing and Learning Center
Thanks to all for the video, and the project description. The project looks like it creates lots of great opportunities for participants.
I'm curious-what kind of certification do participants achieve upon completing the program?
Also, how are you thinking about program impacts/outcomes? Again, the students are clearly engaged in some great activities and experiences, so could you describe what kinds of analysis/evaluation you are using to measure impact?
Iris Wagstaff
Gabriele Haynes
ERN Program Evaluator
Hello and thanks for your comment/question. I am the external evaluator and happy to talk more about the assessment. First, the certificate they will receive is a "Graduate Certificate in Data Science" from the University.
To measure impact, we look at self-efficacy, sense of belonging, science identity, and desire to pursue STEM careers or persist in STEM. We measure student perceptions of these metrics before and after their participation in the program and use basic mean comparisons to measure change and test for statistical significance as well as effect size. These metrics are linked to improved student outcomes and persistence in STEM. I am happy to talk further if you have more questions.
Iris Wagstaff
Allison Gonzalez
Sarah Haavind
Senior Research Project Manager
Hello DS Professional Certificate Design and Development team! As Jeff notes, this project appears to offer great - and a variety of - opportunities for participants. I imagine the integration of data science experts working directly with faculty and students is potentially enriching all around. Can you tell us more about the sorts of projects that are engaged? Are the experts involved with designing the curriculum and if so, in what way? If not, who is framing the tasks? Thanks in advance, I look forward to learning more.
Iris Wagstaff
Gabriele Haynes
Carmen Caiseda
Professor and co-Pi of MSEIP-DS Inter
Hi Sarah! I will re-write Alvaro's answer.
Thank you for your questions. The experts have been fully integrated in the design of the data science certification, that was just approved in past days by the university. The curriculum was improved not just with their recommendations, but with the experiences observed during the Summer Institute, in terms of the basic skills needed and the amount of material in each course. The field of data science is diverse, covering many applications in other sciences, but most employment offers are in businesses. Projects have been mostly in modeling for businesses or in machine learning, in the area of image recognition. We are in contact with the people of analytics in banks and insurance companies in Puerto Rico, for internships for students and also to include their employees in our courses. We have collaborated in the past with labs and research universities which have accepted our students of applied mathematics and computer science for workshops and summer internships. We hope to continue and enhance these opportunities in the future for the students of data science.
Iris Wagstaff
Sarah Haavind
Gabriele Haynes
Alvaro Lecompte Montes
Professor
Thank you for your questions. The experts have been fully integrated in the design of the data science certification, that was just approved in past days by the university. The curriculum was improved not just with their recommendations, but with the experiences observed during the Summer Institute, in terms of the basic skills needed and the amount of material in each course. The field of data science is diverse, covering many applications in other sciences, but most employment offers are in businesses. Projects have been mostly in modeling for businesses or in machine learning, in the area of image recognition. We are in contact with the people of analytics in banks and insurance companies in Puerto Rico, for internships for students and also to include their employees in our courses. We have collaborated in the past with labs and research universities which have accepted our students of applied mathematics and computer science for workshops and summer internships. We hope to continue and enhance these opportunities in the future for the students of data science.
Iris Wagstaff
Sarah Haavind
Gabriele Haynes
Carmen Caiseda
Professor and co-Pi of MSEIP-DS Inter
I will like to add to this that Alvaro as the PI of this project and community, has been leading the effort on developing the Data Science Professional Certificate and other not-for-credit options. I enjoy the fact that we are building a "community of practice" around Data Science that is a perfect discipline to mix a diverse pool of talents and disciplines that learn from each other as they work together.
Sarah Haavind
Gabriele Haynes
Carmen Caiseda
Professor and co-Pi of MSEIP-DS Inter
Dear visitors, welcome to the Video Showcase. We are building a Data Science Community of Practice starting at our private 4-year HSI Institution the Inter American University of Puerto Rico. This project has been built through the MSEIP-USDE grant. We want to acknowledge the support of the MSEIP Program Officer Dr. Bernadette Hence. We also want to thank all the participants of the DS-INTER program: speakers, faculty and students that make up this community as we learn, challenge each other and grow together. We appreciate all your comments.
Iris Wagstaff
Gabriele Haynes
Bhaskar Upadhyay
Associate Professor
I like the multiple entry point aspect of the project for the certification program. I'm curious how students are mentored to take which entry points - is there a process of guiding students for the most suitable certification? I think earlier someone has already mentioned, how is the curriculum decided and how the topics for certification are chosen - based on demand or current trends in data science? I liked the premise of certification, which is needed a lot in the current environment.
Iris Wagstaff
Gabriele Haynes
Carmen Caiseda
Professor and co-Pi of MSEIP-DS Inter
(Hi Bhaskar! I am just transferring Alvaro's answer to you here)
Thank you for your comments. This program is directed to people from diverse areas and experiences. The faculty themselves, is highly diverse, from mathematics, statistics, computer science, information systems, mathematical biology and even from psychology, with interest in data science principles and applications. Therefore, we did not wanted to have strength requisites in mathematics or programming, although some are needed and developed. We have included a lot of examples trough which people who already have some knowledge can go in depth quickly, while others can get the motivation to learn more advanced mathematics or programming skills. As there are many resources (software and public data) available, some people can go straight to productivity, without all the details, and others can work more on the concepts and ways to do things. This is particularly so in the areas of statistical modelling and machine learning. We have worked the projects in small teams and observed how the diversity in the team actually provides more insight an synergy. How the program evolves with the trends in data science depends a lot in the faculty and students. We hope to maintain good contacts and communication with our experts and with other institutions.
Alvaro Lecompte Montes
Professor
Thank you for your comments. This program is directed to people from diverse areas and experiences. The faculty themselves, is highly diverse, from mathematics, statistics, computer science, information systems, mathematical biology and even from psychology, with interest in data science principles and applications. Therefore, we did not wanted to have strength requisites in mathematics or programming, although some are needed and developed. We have included a lot of examples trough which people who already have some knowledge can go in depth quickly, while others can get the motivation to learn more advanced mathematics or programming skills. As there are many resources (software and public data) available, some people can go straight to productivity, without all the details, and others can work more on the concepts and ways to do things. This is particularly so in the areas of statistical modelling and machine learning. We have worked the projects in small teams and observed how the diversity in the team actually provides more insight an synergy. How the program evolves with the trends in data science depends a lot in the faculty and students. We hope to maintain good contacts and communication with our experts and with other institutions.
Iris Wagstaff
Gabriele Haynes
Sarah Haavind
Isaris Quinones Perez
Hi,
My name is Isaris Quiñones from Puerto Rico. I saw the video and I was wondering what types of decision can be make with this learning in data science? This could be use to make legislation or make better decisiones that benefits people?
Also, I want to ask How is ethics integrated in this certificate?
I hope the best for this initiative!!!
Sarah Haavind
Carmen Caiseda
Professor and co-Pi of MSEIP-DS Inter
Hi Isaris! Thank you visiting. There is a lot to gain when we learn data science skills at all educational levels. Particularly in PR we can help institutions to make better decisions based on data that with the input of experienced stakeholders and subject-matter experts will produce useful course of action. These institutions include government, non-profits, and business of all sizes within all areas of socio-economical interests. Thank you for bringing "ethics". In this certificate we contemplate to include at the very beginning ethical and unbiased use of data, secure data management. We also adopted a code of conduct for our community of practice in our DS- Summer Institute.
Sarah Haavind
Kathryn Kozak
Your program sounds great to help students learn data science. I am wondering what professional development was offered to the faculty to develop the different programs that you off, and what professional development do you have for the faculty to learn about data science topics and how to teach those topics?
Gabriele Haynes
Carmen Caiseda
Professor and co-Pi of MSEIP-DS Inter
Hi Kathryn! Faculty and students participate in the Summer Institute and receive the same boot-camp workshops from our expert speakers. They are encouraged to mentor students in the Group Presentations, and sometimes the even become presenters together with their students, when they are very excited. For Data Science teaching skills we like Data Camp and The Carpentries that are pioneers in what is the most effective and well structured form to teach about working with data at a well planned pace, particularly when coding that is appealing for beginners. Thank you for your stimulating questions!
Sarah Haavind
Gabriele Haynes
Iris Wagstaff
Great job on this project and the video. It looks like this project provides several high-quality opportunities for students that include both educational and career training. Data science has been an emerging field with high potential, especially for students who have historically underrepresented in STEM. The post-Bac training is also a great way to extend learning without entering into a graduate program. I also appreciate the endless opportunities that data science can provide for institutional transformation. Thank you for this work!
Gabriele Haynes
Carmen Caiseda
Professor and co-Pi of MSEIP-DS Inter
Oh, I am moved by your kind comments. I wish you the best as we share the passion for inclusion, diversity and equity in STEM that makes our community a better place we can be so proud of!
Gabriele Haynes
Christine Delahanty
This is an excellent certificate program in the very important and growing field of data science. I like that it is post BS degree. Many students are now seeking certificates and certifications instead of degrees. How valuable is this certificate program to local industry? I ask because we are developing certifications and certificate programs at the request of industry partners, and they have been very encouraging. Also, are all the students with BS degrees in this program STEM majors? What other kind of BS degree recipients have participated in this cert. program?
Gabriele Haynes
Carmen Caiseda
Professor and co-Pi of MSEIP-DS Inter
Hi Christine! I have been following your work. Thank you for posting. We are building the industry advisors and would love to hear how you were able to find these encouraging group. Data Science skills are valuable but volatile in the sense that it is a continually changing arena, and more students are graduating with better Data Science/Analysis skills from college. We do not require for all candidates to be STEM but it will help to have basic statistics and mathematical skills. The Certificate Program has been approved locally and now awaiting for approval from external authorities.
Gabriele Haynes