NSF Awards: 1902568
EDC's Oceans of Data Institute (ODI)’s NSF ATE project, Mentoring to Support Designing and Launching of New Data Science Career Pathways at Community Colleges, has just entered its final year of assisting the faculty of two-year colleges in developing data science programming that is aligned with local industry needs. This alignment is crucial, as community colleges are tasked with the preparation of students who, according to experts, intend to remain living in the immediate area after graduation. By providing a process that maps employer’s needs to the college’s curriculum design, the project ensures that the data program provides students with skills that are already in demand.
In addition to providing direct support to six community colleges through a mentorship program, we've expanded the reach of the project by creating a community of practice for community college faculty & administrators interested in developing data programs.
Sarah MacGillivray
Associate Project Director
Hello, and thank you for viewing our video. Our project assists 2-year colleges exploring the development of data programs and courses with the tools they need to develop successful, industry aligned programs. By following our pathway development process, colleges can assess and align their courses with the needs of local employers, ensuring students are provided with the knowledge and skills that are in demand. Our project is in its final year, and we are interested in sharing our resources and connecting community colleges engaged in this work.
Brianna Roche
Carmen Caiseda
Hi Sara, although we are not a Community College, I know we can greatly benefit from the pathway development process. Our students are mostly commuters, and we seek to increase employability skills through our newly developed Professional Certificate program. Thank you for sharing your work!
Majd Sakr
Great work, thank you! Would love to learn more about what you have learned from industry about the knowledge and skills needed for your trainees to become job-ready.
Sarah MacGillivray
Associate Project Director
Thanks, Majd! The skills are captured in the following report: Profile of the Data Practitioner which was developed with input from a panel of experts from industries including biotechnology, finance, law enforcement, health care, agriculture, and public policy. Our Tools for Creating a Big Data Career Path includes gap analysis tools for both the school and employer, and in comparing these faculty are able to identify “gaps” in their existing program offerings as well as revealing skills that are covered in the curriculum but are not priorities for employers.
Michael Harris
Associate Professor
Hi Madj, I will describe the process from a faculty standpoint.
After the Profile of a Data Practitioner was created, different individuals who work in the data industry reviewed the profile. They rated each item in the profile based on expected knowledge levels of a middle skill data employee coming from a community college. Each item was totaled, and a heat map of the profile was created. The heat map was used by faculty to create learning outcomes for courses based on industry needs. After the coursework was developed, industry was called in again to review any areas missing in the coursework with a gap analysis. The analysis identified areas or both weaknesses and strength, which helped finalize the content in the programs.
Christina Titus
Such great work! This aligns with the grant work of IT Skill Standards 2020 and beyond. We are creating skill standards for hard-to-fill IT job clusters. Two of our six areas are Data Analytics and Data Management. We use a very similar method! Thank you for sharing; I look forward to looking thru your material!
Ann Beheler
This work is quite similar to ours. And, we are working with at least two of the mentee colleges to further expand their industry engagement. Kudos! Thanks for sharing your resources.
Joyce Malyn-Smith
Distinguished Scholar
Thanks Ann - Our work on developing pathways to data science careers that are aligned with industry expectations has been extremely successful. On another project we are working with high schools in MA to integrate foundational data science skills into social studies Civics projects and developing courses in Data Visualization and Python+Data which will connect to our community college data science programs in MA. The colleges in this Mentoring project are linchpins in our data pathway development effort,
Sarah MacGillivray
Associate Project Director
Thanks Christina and Ann! Our work is very similar, we will definitely be sharing your resources with our community of practice.
Joyce Malyn-Smith
Distinguished Scholar
What challenges are you facing in developing your data science programs?
Ann Beheler
Hi Joyce and Sarah - Our colleges have difficulty keeping curriculum up to date, so we are teaching them to work with their employers (their BILT team) on an annual basis to tweak their content.
Gerhard Salinger
Former Program Officer
Templates for developing courses for industry-aligned, middle-skill jobs in data science should be helpful. I am a co-PI on a project to learn about the mathematical competencies needed by technicians in the manufacturing work place. We plan to develop scenarios of what technicians do in the workplace as a way to encourage deeper conversation between industry representatives and technical faculty on the needed mathematics. Have you learned about the middle skill occupations available to two-year college educated technicians particularly in the manufacturing work place? Who hires them? What do the technicians do?
Michael Harris
Associate Professor
Hi Gerhard, I would love to hear your insight about mathematical requirements for two year colleges and data science. One of the struggles for community college data science is the meshing of various mathematical concepts and teaching it all in a 2 year program. Right now, our students take Pre-Calc (if needed), Calc I, Linear Algebra, and Statistics. Ideally, a "Math for Data Science I & II" course would be created where students are exposed to the concepts needed. I have had discussions with Nick Horton (Amherst) and Ben Baumer (Smith) about this very topic and how to address it.
To answer your questions, in the Boston area we don't place many students in manufacturing, but usually more technical fields. We have placed students working in finance, bio-medical, renewable energy, health care and other technical fields. Traditionally, students going to industry with an AS degree will be doing the grunt work of data cleaning and mining. The idea is they will alleviate the tedious which allows the higher paid data scientists to spend their time doing the analysis.
Carmen Caiseda
Mason Lefler
Associate Vice President for Educational Innovation
Hi Gerhard,
We are definitely dealing with the manufacturing analytics issue in Utah. At Bridgerland Technical College we are in the process of developing two courses which are both title "Manufacturing Analytics". One course will be for data technicians looking towards manufacturing and the other course will be for automated manufacturing/controls engineering techs looking towards data analytics. We are in the process of building both courses.
Mason Lefler
Associate Vice President for Educational Innovation
Here is the course description for the controls engineering techs:
This course will provide students with experience working with data as a control systems technician. Students will become familiar with the types of tasks which will be required of control systems technicians working with data in manufacturing. Students will learn several manufacturing data concepts while using multiple sets of data based on real-world scenarios, and apply the principles learned using real-world systems.
Objectives:
Mason Lefler
Associate Vice President for Educational Innovation
Here is the course description for the data technicians:
The Manufacturing Analytics course provides students with experience working as a data practitioner in the field of manufacturing. Utilizing real-world situations, they gain experience with the types of tasks which are required of data practitioners working in manufacturing. Students go through the data cycle with multiple sets of data and different scenarios that can arise in manufacturing situations. Students optimize manufacturing data and practice predictive maintenance. They access a Programmable Logic Controller (PLC)-driven manufacturing system to a database and process that data as though in a live working environment utilizing data analysis programs and techniques. Students who complete this course are able to work with manufacturing data.
Objectives:
Carmen Caiseda
Mason Lefler
Associate Vice President for Educational Innovation
I would love to stay in touch with your developments and collaborate. We are just getting started and sounds like it would be mutually beneficial. We are also going through a BILT knowledge and skills analysis with our advisory board where they will be ranking the needed knowledge. This will include questions about manufacturing and statistical skills. We are very willing to share what we learn.
Carmen Caiseda
I believe the advisory board is a great idea that we should also implement in our Data Science Professional Certificate program. Great ideas from your project. Thank you for sharing.
Ann Beheler
And, since I do so much work in multiple echnician areas, I want to keep up with all developoments, too! I am also happy to share what we have created!
Joyce Malyn-Smith
Distinguished Scholar
Gerhard - Great to hear from you!! As you know, over the years we have come across a number of approaches to identifying the academic competencies needed by technical workers. No doubt you have also. Most start with a concrete description of what the technician needs to know and be able to do. This often takes the form of a profile describing the duties and work tasks as well as associated skills, knowledge and behaviors of that specifically defined occupation. Once the work tasks are agreed upon by experts in the field, then it is easier lift identifying the academics needed to perform those tasks. It is when the work is ill defined or there is little agreement on what the work looks like - that the academics become difficult to identify. We have had great successes in developing occupational profiles of both traditional and emerging technical occupations (such as the Data Practitioner) and would be happy to share both our process and examples.
Carmen Caiseda
Dear Joyce, I would also love to see your occupational profiles examples and process. I believe we would greatly benefit from your work. Thank you for shaing.
Leana Nordstrom
Associate Project Director
Carmen, thank you for your interest in the occupational profiles! Both can be found on the oceansofdata.org website. The Profile of the Data Practitioner is focused on the skills and knowledge for middle-skilled data workers and the Profile of a Big-Data-Enabled Specialist is our first and general occupational profile for an "individual who wrangles and analyzes large and/or complex data sets to enable new capabilities including discovery, decision support, and improved outcomes."
Margie Vela
CEO & President
This is an important initiative that is transforming education to meet the needs of local industry and national economy. Higher education is facing some of tough decisions as students and industry are requesting better alignment of educational priorities and industry needs. As you are transforming programs, have you noticed any changes in alignment with four-year programs? Do you think that this type of alignment for universities is feasible? If so, what do you think would be the greatest challenge(s) for this effort to succeed?
Joyce Malyn-Smith
Distinguished Scholar
Because working effectively with data has become foundational across all industry sectors to perform technical work as well as to operate successful businesses, there are many more options for transition from a community college data analytics program into 4 year university programs. We don't look only at transition into formal data science programs at the university level but also to business analytics, biosiences, financial services and other programs in which working with data is essential. It is becoming more widely recognized that having solid data skills today provides workers with a solid grounding and enables people to be more successful in all types of work.
To answer your question re challenge: In my view the greatest challenge today is to help employers recognize the emergence of a middle skilled data workforce and seek graduates from community colleges as well as from universities to fill their data workforce needs.
Mary Slowinski
Really interesting work! Our ATE project (Working Partners Project & Workshops) supports educators with strengthening their skills at initiating and sustaining partnerships with industry and I'd really like to connect and see if perhaps one of the leadership team would be willing to share their tips and successes on building the industry connections that have proven so useful to these efforts. Who might be the best team member to contact?
Joyce Malyn-Smith
Distinguished Scholar
Mary - Thank you for your interest in connecting. Any one of our mentors or mentees would be happy to share their perspectives on how they connect with employers. What we have found over time is that we need to provide something substantive and purposeful to get employers engaged. Our college partners usually begin their work by connecting with employers and engaging them in a dialog around the Profile of the Data Practitioner (See Mason's earlier post - and James Polzin's comments in the video). Discussions revolve around the question - to what degree do you expect your data team members to .....(insert work task) - do you expect them to know about this? ....perform this task under supervision? ..... perform this task independently and be able to teach it to others? What work tasks are your highest priorities for members of your data team? As the discussion evolves employers are able to make clear what they want/need and educators get a very clear understanding of what graduates need to know and be able to do to be employable in the local economy. As the engagement grows over time, employers understand that they are providing important input into curriculum and when they see that the curriculum includes their input, they are more likely to strengthen their partnership with colleges by offering work-based learning opportunities, and by hiring graduates. Send me an email and I'll connect you with our project partners so you can get their perspective on this topic also. Jmsmith@edc.org
Joyce Malyn-Smith
Distinguished Scholar
To Mentors and Mentees - see Mary's interest in learning more about how you engage employers. What would you like to share with her?
Ann Beheler
Joyce, Mary's work in Working Partners includes and is complementary to the work we do with the Business & Industry Leaership Team (BILT) model. I definitely suggest you connect with her as we already have with some of your mentees. - Ann
Tim Podkul
Senior Research Advisor
This is exciting work, and certainly takes future employment needs into account. The potential for scaling what you have done here is incredible! What a great contribution to the field and community colleges. I am curious if there is an certification or credentialing that accompanies completion of this curriculum?
Joyce Malyn-Smith
Distinguished Scholar
We have not yet moved forward with a credential. However, we do have the groundwork laid to make that happen in the future. Thanks for asking.
Andrea Tirres
Thank you for sharing this interesting work. Can you talk more about the communities of practice that you established -- how where they organized in terms of roles among members, what platforms are you using, what is the level of engagement?
Leana Nordstrom
Associate Project Director
Hi Andrea, Thank you for the question. The community of practice is an open group to faculty and administrators at 2- and 4-year institutions who are developing data programs. I facilitate and plan the virtual meetings, which were originally held monthly and are now held bi-monthly. Two or three of our mentor faculty members attend the meetings to offer their expertise, having developed data programs at their institutions through the previous grant. In addition to our meetings, we have an email listserv and newsletters for sharing resources, information and news. We also use a Google Drive folder and our oceansofdata.org website to share resources that are private to CoP members. The meetings generally have 10 to 20 people join and the discussions and resource sharing has been great.