CPACE Meeting Minutes Date: December 05, 2007 Time: 3:00 p.m. - 5:00 p.m. Location: Michigan State University, East Lansing MI Next meeting: December 19, 2007 Time: 2:30 p.m. -4:30 p.m. Participants listed by group:
General Agenda: (attachment 1) 1. Review minutes from Nov 26, 2007 meeting. There were no changes to the minutes. 2. Review Meeting Purpose Gary: The purpose of this meeting is to help you think about employer
engagement strategies. CSW has extensive experience engaging multiple
employers from a particular industry or like-industries to address labor
market challenges. 3. Labor market information Tammy: We used the areas of disciplines that you sent to find occupations related to those disciplines. The method used is based on classification of instructional programs (CIP) codes and the standard occupational classification system (SOC) code that all labor market information around occupations use. Computer Occupations (attachment 2): We identified four CIP codes as codes that either MSU or LCC are granting degrees. Those CIP codes relate to the occupations shown below as SOC codes. The first step was to determine the industries that we want to target in terms of engagement. The next step is to determine in what industries is this group of occupations most prevalent. The concentration table shows data collected across five geographies. The percentage corresponds to all the people employed in the cluster of occupations and what percentage is on a particular industry. The yellow highlight reflects what the top ten for each geography are. Mark: Where are the universities located in the EMSI data? Gary: They are typically in education services. Tammy: I will look where education services fit in. The numerical table gives the numerical data. The next thing we looked at is how these industries fit into the overall economy of mid-MI (rankings table). The way we ranked the economy was by using a model that considers several factors (refer to handout for the list of factors). Gary: Location quotient is an economic term to understand the employment competitiveness of an industry compared to the state and the nation. It deals with employment rates. Tammy: We rank all the industries in the region (282 industries) relative to one another using the different factors, the individual rankings are added up and the result is an overall score for each industry, then we rank those in the overall economy of mid-MI. This model tries to look beyond employment. Gary: The weights can be recalculated in terms of any factor. What is important with this data is to look beyond employment numbers. Is there a base of employment? Has it been growing? Is it projected to grow? Is it competitive against the state and the nation? and does it pay a good wage? In this model these factors are evened-out. Employment base is particularly important for the CPACE project because one of your concerns is what are the occupations that you are producing? And are the people produced going to find a job in an industry that has an employment base? Mark: Are these weights based on CSW experience? Gary: Yes, we treat everything equally except location quotient. Jon: What is the goal of the weightings? Gary: The goal is to look at multiple factors. We look at a model that goes beyond employment. I want to clarify that the employment corresponds to the number of jobs that are available not the number of people who work in the job. Jeannine: Could you remind me what is historical performance? Gary: It refers to the known historical documented growth of the industry. Jeannine: Back to Jon's question about how is the model useful in the context of this project. We are looking at students that are coming from MSU and LCC and the types of jobs they are taking and how does that relate to what's going on in the mid-MI economy in terms of jobs. By using these data we can look at other variables not just jobs. Gary: For your purposes for example if this is about the
types of employers you want to engage and around what issues, then
beyond the jobs the two things that you might want to consider are, is
it projected to grow? And is it an industry where you (MSU) have some
competitive employment advantage as you may be part of the reason for
this competitive advantage by producing the skilled workers that are
allowing the industry to grow at a higher rate than the rest of the
nation. Tammy: The last pages of the report are about qualitative information about the occupations for example generic descriptions and national trends regarding that occupation. Gary: Let's switch to the engineering occupations. Engineering occupations (attachment 3) Tammy: The process is the same that was used for the computing disciplines. Tom: In a study that I did some years ago, the state of Michigan graduated 4% of the nation engineers and 10% of the nation's mechanical engineers. South-east MI has the largest per capita number of engineers in the USA. Daina: Who uses the definitions that appear further in the document? Gary: The data comes from O*NET which is the US department of labor occupation database. It was created from surveys of incumbent workers across the country from every occupation defined by the federal government and bureau of labor statistics. It looks at different characteristics, skill requirement, education level, knowledge requirements, tasks performed and also there is a description of the jobs. Gary: To answer the question (Daina's) we can only measure industries and occupations that are defined by the bureau of labor statistics. The information from O*NET is used by two major players; first, community colleges use it to inform their curriculum. Then human resources (HR) managers, as a matter of fact O'NET was developed to inform the HR system across the country. It looks at the information in two dimensions importance and level. Tammy: (Walked us through the engineering document). 4. Employer engagement Gary: I believe that we have showed you what we wanted to
show you and now I want to talk about three levels of data to go deeper.
One, is to understand the occupational competitiveness (we showed you
location quotients at the state and national level), we can also show
geographically where the clusters of computing and engineering jobs are
across MI (geographical information system, GIS mapping). Jon: I am losing focus. Our project is focused on the engineering disciplines and computer use within those disciplines to better meet workforce needs. These data is very interesting but very broad compared to the level that we are at. Jeannine: In this project we are starting from a
disciplinary perspective and looking at occupations then we are looking
at the industry sector and from the industry sector perspective we are
looking at the organization level base for these occupations. We need to
survey corporations or businesses and their incumbent and we need to be
able to target which corporations we are going to engage. We are taking
you through the process that we (CSW) use to narrow the focus. Tom: The data from MSU indicates that 60% of our graduates left MI but 70-80 % are within 400 miles, they stay around the Midwest area. Jeannine: We are trying to figure out what our industry base looks like, where are we trying to evolve, what is our competitive advantage, and how engineering fits into this scenario. Jon: And the whole purpose is to feed back to our curriculum. Mark: To some extend we are not worried about filling the mid-MI job market requirements to a particular job but to what degree does the mid-MI job market reflects our national base. What Gary mentioned about task analysis seems to fit this purpose; ultimately we are going to ask what computational tasks the engineers are performing. A starting point is to see what those tasks look like across disciplines, then we need to identify what are the gaps that we need to fill and who is better suited to give us the data or guide us in terms of finding the data to fill the gaps. Gary: Here is an example in the O'NET website (http://online.onetcenter.org/). These are the kind of data that we can aggregate across the occupations. These are very informative to curriculum development. Tom: Many of these tasks we do not include in the engineering curriculum deliberately because these are things that you can pick up while doing the job. For example reading blue prints is incidental and we do not have it in the curriculum. The fundamental technical knowledge is above the tasks. Gary: At any level of information that you need or want,
we can aggregate for you across occupations. This is the kind of
information that we want to have when we talk to employers to get them
to validate or edit using these data as a starting point. Jeannine: Is any of this information validated by people working within higher education? Gary: The data comes from incumbent workers there is no validation process. Every year O*NET reevaluates a percentage of the occupations and re-survey workers. Information about the tools that are used to survey the workers can be found in the O*NET webpage. Tom: When it says mechanical engineering, these are people whose job title is reported as mechanical engineering. Gary: These data comes from the US department of labor,USbureau of labor statistics. The job titles are not reflective of reality. If we are using secondary data we are limited to its restrictions in this case the structure of the titles. Tom: For our purpose here and because we want to match it to curriculum development, When we look here (O*NET) at mechanical engineering we find people whose job description is mechanical engineering, most of them would have a degree in mechanical engineering. But several may have other degrees, the concept of mechanical engineers working as mechanical engineers is decreasingly true and we have to consider this. Gary: You are raising a critical point. Any research would
have to combine secondary data with primary data. This is critical for
the next step which is when we talk to employers or employees we need to
know what is it we want to know from them. Tammy: We looked at cross walks that associate with the occupations listed. The cross walk looks at the CIP codes and associates those with occupational codes which are the sort of titles listed in the engineering occupation attachments. Gary: I want to be careful here and stay on target on why we are collecting this information. Potentially what we want to use these data for is to understand across the cluster of occupations what are the major activities they are engaging in for the purposes of being more informed about who we talk to and what we talk about. As much as we want to answer your specific questions we want to stay focused on what is it about these data that we want to use to inform our engagement strategy? Jon: You are using the intersections (across disciplines) to inform what engineers do and then go and talk with the companies about those tasks. Have I got the picture? Gary: Yes and the reason is because if we go with a blank slate we tend to get incoherent answers. If we say, this is what we know about the occupation tell us if this is true, we get farther faster and more accurate information. Jeannine: The difference in this project is the team that is compiled here, we are going to have an interim step where we connect at the department and discipline level (MSU, LCC) to inform the process. We have the academic institutions involved in the process which is something that we usually don't have. Mark: We are going to use all these information about tasks, skills and abilities to try and distill the underlying computing concepts that potentially affect curriculum. We will be looking at features that can be generalized across an engineering curriculum. Gary's point is that this allows us to frame the conversation, this is a starting point to talk to employers and employees to get some sense of where they see their industry sectors going, what's common in the industry is it about new skills? or is it about shift of emphasis? Tom: The tab on tools and technology (O*NET website) could be more helpful than the tasks as it has common application processes that we have in our curriculum. Gary: Let me show you another feature on O*NET, they have 'anchors' which are representations of what the various levels are. The anchors give some context to the numbers (We looked at the different levels in the website for examples on what the scale anchors shows. This tool can be used only for some of the characteristics). Cindee: Gary, it is 4:30 now. What do you propose in terms of next steps? Gary: There is some interest in these data (O*NET) so I propose that using the two clusters of occupations, computing and engineering, we aggregate the data around work activities and relate that to the scale and I also suggest we do GIS mapping to show where in mid-MI these occupations are physically clustered. Tammy: Are you interested in the computer occupation group or only in engineering? Mark: To the degree that in MSU and LCC computing is a part of engineering requirement. I think we would not want to exclude computing science. Jon: Yes but there are a lot of IT that does not really fit. Tammy: I suggest looking at the list of computer occupations that I compiled and define which ones you want us to focus on. Tom: The question I have deals with GIS mapping around mid-MI only. We do not have a mid-MI curriculum we have a 400 miles radius upper mid-west curriculum. Gary: We can pick any geography to do the mapping of where the occupations are clustered. Mark: We want to be more representative of a national scenario. Tammy: In terms of the industry concentration you want to look at the national level. Is there another geography that you want us to look at? Tom: You would catch many with MI, OH, IL, IN, WI, MN Gary: Let's start with upper mid-west because as we do a GIS if we look at the whole nation you will see the natural clusters. We will start with the mid-west for the next meeting and see then what other areas you want to look at. Tom: You will get most of the places our students work; you will miss aero-space they go west for that, you will miss chip manufacturing but you will get all chemicals, all kinds of construction, manufacturing, and some electronics. Gary: I want to make an important point, all of the data in O*NET is national and this is an important assumption that we make when we talk to employers. Tammy: What I suggest is to add a column to this 'in what industries are these occupations employed' that will reflect the broader geographic area for the purposes of targeting who you want to talk to. Gary: I want to talk about the larger issue of the employer engagement strategy as we think about these data. When you gather employers do not start with a survey. Also you want to think about who among employers you want to target, do you want to target CEOs, HR managers, frontline supervisors, employees? All four of these are slightly different conversations. When we gather CEOs they value visioning what is going to happen to the industry together with other CEOs. Jeannine: We need to make sure that we are not duplicating in this project anything you are already doing with the other advisory boards that you convene and/or we need to think how do we leverage or use those advisory groups to get important information. Gary: This is important because if these advisory groups are together and have met and have some commitment then you may be able to start a survey with them but we would want to help you think about that. Tom: We have a director of employer relations (*Motschenbacher)*at the college of engineering and I think it is important to have him at one of these meetings. Jon: We need to finalize the advisory board invitation. Jeannine: We are sitting with two major questions: First, we need to narrow the scope of the project in terms of which engineering disciplines we are going to include. Tom: Five disciplines cover 85% of all engineering; civil, mechanical, electrical, chemical and computing by some name, the others are offshoots in one way or another of these disciplines. 5. Advisory board membership Jon: Do we have a final approval of the advisory board invitation? Tom suggested some changes. Tom: Are we going to hand pick the people for the advisory board and send them an invitation or send it as a job announcement? Mark: It has to be a one on one personal contact. Cindee: We have the talking points that we use to engage in the conversation but we can have an invitational message that we each create. Daina: Given the discussion to focus on the engineering disciplines, one of my assignments was bio-systems engineering and I am wondering if it is worth the effort. Cindee: Our reach has to be broad to reach the required number of members. Tammy: I need to get some refinement in the occupations and CIP codes that should come from the educational programs we will look at tasks, activities and technology use. I will e-mail the group list and ask for input on this issue. Gary: We have decided to look at the engineering occupations and look at the computer occupations with the word engineering in it. Is this a final decision? Tom: May be there are a couple more of the computer occupations to be added. Tammy: I will look at program completion numbers from MSU and LCC by CIP code. Daina: As a next step we can do cross mapping to the ABET learning outcomes to look at occupations and compare to the features listed in O*NET. Lisa: How often MSU does this kind of curriculum evaluation? Tom: Following ABET procedures the curriculum and outcomes are put on the table in great detail every six years and every two or three years as part of a process and in some level every year but not in a robust, detailed, formal manner. Daina: It has to do also with how the workforce changes. Tom: External forces are important, for example employers or visiting groups come in and complain about something regarding our graduates. Daina: Sometimes the push comes from professional societies as well. Louise: At LCC is every two to four years. In computer science we hold it at the beginning of a two year cycle. Jeannine: I was wondering in terms of knowledge creation and tools and technology development, how much of it is driven from an industry perspective and how much of it is happening from within the educational institutions. Tom: Ultimately it is driven by corporations and employers. ABET is an organization composed of professional societies and they in turn are the employers and practitioners. Jeannine: This was one of the ideas we talked about initially, if there's great stuff going on here at MSU in terms of computing related to engineering how does any of that feed into the economic development of the region. Tom: The push comes from outside, corporations and employers; delivery comes from inside. But I don't think computing curriculum drives economic development in the state, it could certainly be a rate limiting factor. Jeannine: In terms of the advisory board we are at a point where we have talking points. Cindeee: I'll make the final version. The names that have been proposed for the advisory board will be updated. Jeannine: Do we want a formal letter from Tom? Jon: Could be a good idea so they get Tom's formal invitation and the information packet and each of us would do a personal invitation. Jeannine: The next meeting we should focus on trying to finalize the advisory board discussion. We will prepare a draft letter from Tom, a final version of talking points and current version of the list of employers. We should also talk about the quarterly meetings for the advisory board, the purpose of those meetings Jon: We should also set specific dates to inform people. Tom: I want to leave you with one thought. For example if
you pick mechanical engineering graduates and see what they do with that
title and this perhaps is one of the important reasons to look for the
commonality between engineering disciplines because there are increasing
numbers of engineering graduates that go into jobs that don't have
engineering job titles. They are being selected because they have the
same traits and skills that are in the job titles. First you find the
commonality between the four or five disciplines and then you find if
there is something in common with this out-group. Gary: Has there been an effort to survey the alumni of the disciplines to see where they are geographically and what field are they in and ask about the relevancy of their education to the field they are in. Tom: We do that on recurring bases also as part of accreditation. We had a lapse but are preparing to start it again because when we do accreditation we look at outcomes and objectives and our objectives are that the curriculum has to prepare graduates for the skills that we expect them to be doing a few years out and to verify that they are able to do those things we survey people depending on the department two to five years out to Gary: If you are getting ready to do it; is it within the time frame of this project and is there a way to align it with CPACE or are the set of questions specific because of the accreditation process? Tom: The set of questions in each department are tied to the objectives of the department so it is not possible to tinker with the surveys, but the surveys would have insight that is applicable to the project. We will probably have a set ready for this spring. Gary: Could we identify people in a way that we might be able to follow up with a different set of questions that would more specifically inform this project? Tom: For past surveys is not possible but in the process of the department doing the surveys we could find some people. Gary: And this may be a good way to think about a follow up mechanism. Jon: When you have bills please send them to me. Summary and key points Labor market information summary - The model used to generate the labor market information data looks beyond employment numbers; important elements: - Base of employment - Growth (current and projected) - Competitiveness at state and the national level (location quotients) - Wages - Particularly important in the context of the CPACE project: - Employment base as it relates to industries/occupations that employ engineers and the computational tasks they are performing. - How do these industries compare to the overall economy? - Specific competitive employment advantage related directly to MSU/LCC - Use available data to validate it and to determine gaps in information (unavailable data) in order to better target the collection of primary data. What region are we going to focus in? - We need to broaden from a regional to a state perspective because the mid-MI base is not sufficient to draw a connection between what is happening within MSU and LCC engineering disciplines and what's going on in MI's economy. - The data from MSU indicates that 60% of our graduates left MI but 70-80 % are within 400 miles, they stay around the Midwest area. We have a 400 miles radius upper mid-west curriculum. Important regions are: MI, OH, IL, IN, WI, MN. Engineering disciplines to include: - Five disciplines cover 85% of all engineering; civil, mechanical, electrical, chemical and computing. Features that can be generalized across an engineering curriculum: - O*NET is the US department of labor occupation database. It was created from surveys of incumbent workers across the country from every occupation defined by the federal government and bureau of labor statistics. O*NET data can help us identify what computational tasks engineers in different disciplines are performing, ultimately we want to extract the underlying computing concepts that potentially affect curriculum. - From the O*NET data we will focus on tasks, activities and technology use. - As a next step we can do cross mapping to the ABET learning outcomes to look at occupations and compare to the features derived from the O*NET data. Cross-walks: - In terms of the O*NET data, the job titles are not reflective of reality. - Secondary data has to be combined with primary data. A strand of critical questioning is to ask people about their degree, what their current occupation is and how does that relate to their discipline. - There are increasing numbers of engineering graduates that go into jobs that don't have engineering job titles. It would be important to determine what they have in common with the other engineering disciplines. Employer engagement strategies: Labor market information data is effective to: - Identify types of employers to engage and identify what issues we need to talk about. - Identify unavailable data to better target the collection of primary data. - Available data serves as a starting point that allows us to frame the conversation, when we talk to employers and employees. - It is not a good first strategy to begin engagement with a survey. First they need to be engaged and bought into the larger mission of the project before they are willing and able to respond to surveys. - It is important to think about who among employers you want to target as different groups determine slightly different conversations. Convening of the advisory board: - We have a final version of the talking points/information packet. - We need a formal invitation letter from Tom. - The person making the contact will have a personal invitation.
Action items: CSW: - Using the two clusters of occupations, computing and engineering, we will aggregate O*NET data around work activities specifically tasks, activities and technology use and relate that to the anchors scale. - GIS mapping to show where are these occupations physically clustered in the upper mid-west. The geography to look at includes: MI, OH, IL, IN, WI, MN - Add a column to the industries table that will reflect the
broader geographic area for the purposes of targeting who we want to
talk to. Cindeee: - Update the names that have been proposed for the advisory board. - Prepare a draft of the formal letter from Tom to the advisory board. MSU/LCC: - Look at the list of computer occupations that Tammy compiled and define which ones Gary/Tammy need to focus on.
Logistics: Next meeting: Wednesday December 19, 2007 Time: 2:30 p.m. - 4:30 p.m. Location: Michigan State University,East Lansing MI |
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