Tuesday, August 01, 2017

Job-Oriented Online Programs (JOOPs)

Last update: Sunday 8/7/17

This note provides an introduction to packages of online courses for professionals who want to acquire new job-related skills that will enable them to change their career paths. Written in the summer of 2017, the details in this report may not reflect current program data; but its conceptual frameworks are still relevant 





These professionals are not seeking knowledge for its own sake or looking for credit towards degrees from accredited institutions. They are lifelong learners who know know that state-of-the-art skills earn larger paychecks, whereas obsolete skills risk pay cuts and/or unemployment. As part-time students, they also want to manage their study time efficiently. 

I recently retired from a 40 year career as a tenured member of the faculty of a prominent university and as a member of its senior administrative staff. In order to prepare for a new (final?) career as a part-time consultant, I have been taking job-oriented online courses.  My participation in these courses enables me to bring a participant-observer's perspective to this discussion that I have rarely encountered in my continuous reading of a wide range of higher ed publications. I have become a student again, but one who has the benefit of a former insider's understanding of what really goes into the political sausages commonly known as "higher ed policies" ... :-)

I think it's unlikely that useful skills can be learned from a single short course (4 to 6 weeks). Ambitious professionals could design their own package of courses by picking a good MOOC here, followed by a second from over there, then a third from out yonder, etc, etc, etc. But this would be an inefficient use of their study time if only because they probably don't know enough about the new material (new to them) to be able to determine the most appropriate sequence of courses or to judge which MOOCs provided the best coverage of the material. Cherry-picking MOOCs is also inefficient because MOOCs developed by different subject matter experts who were not in communication with each other during the development of their MOOCs will probably use inconsistent terminologies that will confuse new students (at first). 


So it's probably best to choose packages of MOOCs, i.e., MOOC programs, the same way that full-time students choose degree programs ==> by focusing on the reputations of the providers of the programs, the reputations of their instructors, their fees and time requirements, and the mentoring, job placement, and other support services offered by the providers of the programs.




I. From MOOCs to JOOPs

The original "MOOCs" (massive open online courses) enrolled thousands, sometimes hundreds of thousands of students; hence they were "massive" when compared to traditional enrollments. MOOCs were open to anyone who wanted to enroll, and MOOCs were online. The number of MOOCs is still increasing from one year to the next, but a substantial subset has evolved into JOOPs (job-oriented online programs).
  • Enrollments in JOOP courses are not massive; indeed their enrollments are closer to enrollments in large traditional courses.
     
  • Whereas most MOOCs were offered as free-standing courses; JOOPs are typically offered in packages of carefully sequenced MOOCs. Students must pass all of the courses in the package to earn the program's certificate. Successful completion of a program means that students have acquired a very specific set of job-related skills.
     
  • Some JOOPs are not open, i.e., students who do not have appropriate prerequisites are discouraged from enrolling or not permitted to enroll in the courses.
     
  • MOOCs were usually too large for their instructors to answer all of the questions posed by their students. So most MOOCs implemented some kind of discussion forum wherein students could help each other gain a better understanding of the course materials. MOOCs were also too large for their instructors to evaluate all of the open-ended homeworks and projects submitted by their students. Some used peer evaluations wherein students evaluated the submissions of other students by applying detailed rubrics provided by the course instructors. By contrast, some JOOPs have addressed both of these issues by hiring experts who answer students' questions and evaluate students' projects and other submissions according current best practices in the field.
     
  • It was never clear how MOOCs would recoup their sponsors' expensive development costs, much less become profitable. By contrast, some JOOPs have already become highly profitable operations by charging substantial tuition and fees for their certificates.  
Full disclosure #1 ... 
  • "JOOP" is not a widely accepted name for job-oriented online programs. I made it up. I made it up because it seems to me that this particular subset of MOOC programs is evolving in predictable directions that other kinds of MOOC programs are unlikely to follow. If someone comes up with a better name for these programs, I will use that name. 
  • My hope is that a distinct name will encourage prospective career changers to switch their focus from individual MOOCS to the kinds of packages of MOOCs plus support services that will enable them to change their career paths and then charge their employers or clients the going market rates for their services. 

II. Job-Oriented Courseloads

What should career changers look for when selecting JOOPs? I ask my readers' indulgence to allow me to consider this question in the context of an imaginary conversation that I might have had with an imaginary former student in my old office were I still a member of the faculty. In the dialog below, I refer to myself as "Dr. B" and my hypothetical student as "Robert". The dialog assumes that Robert is one of my former students who earned a masters degree from my university.

Robert: Good morning, Dr. B. Thanks for seeing me on such short notice. I've been wrestling with a career decision for the last few weeks and making no progress. So I'm hoping you can help me clarify my thinking.


Dr. B: Good morning, Robert. Great to see you again and yes, I will be glad to help you if I can. What's your issue?


Robert: I'm thinking of changing jobs. I still like what I'm doing, but as you had warned us in every one of your classes, information technology will disrupt all professions, some sooner than others. I can see this disruption coming to my field within the next two or three years, so I want to get ahead of the wave in order to ride the wave instead of being crushed by it.


Dr. B: Are you thinking of going back to school full-time to earn another masters degree?


Robert: No. I can't afford to become a full time student, nor do I think I have to. I don't want to change fields; I just want to move forward in a different direction. So I just want to add a few important new skills that will enable me to change direction.


Dr. B: How much time can you invest in part-time study every week?


Robert: Around 10 to 15 hours, but 20 plus hours during peak study periods.


Dr. B: OK. I think it might be useful to frame your issues using the old notion of credit hours. I usually subscribe to the newer thinking about competencies, rather than credit hours. But in this case I think credit hours will help us frame your challenge more efficiently, provided we don't take our conclusions too literally.


Robert: Sounds good to me. If I understand what you're suggesting, my decision not to pursue a masters degree could be restated as my thinking that I don't need to take as many courses as would be required for a masters.  A masters would allow me to jump from here to somewhere over there, but I don't want to jump; I just want to "pivot". 


Dr. B: Right. Given that you have limited study time each week, let's hope that you can find a suitable online program because an online program wouldn't require your spending any of that limited time commuting to and from campus for classes. So let's assume that a full-time masters degree would take two years wherein you were enrolled in four 3-credit courses per semester. This means 12 credits a semester; two semesters per year means 24 credits per year; and two years means a grand total of 48 credits.


Robert: In other words if I wanted to change fields, I would take 48 credits; but a pivot should require a lot less, say only two or three 3-credit courses = 6 or 9 credits. 


Dr. B: Yes. 


Robert: As I recall, students taking a one credit face-to-face course were expected to study two hours outside of class each week. So a three credit course met three hours each week and required 6 hour of study at home.


Dr. B: Yes, that was the old thinking. Of course there are no class sessions in an online course, so a three credit online course would require the full 9 hours of study each week. 


Robert:  In the last few weeks when searching for online programs, I've noticed that most of the job-oriented programs offer courses that are much shorter than a 14 or 15 week semester. Furthermore, most of these courses estimate that the required study time is only 5 to 10 hours per week. So I'm looking for a job-oriented program whose many short courses would add up to roughly the same content presented in four 3-credit courses. 


Dr. B: Yes, you need to convert the total number of hours in these short courses to the time to earn credit-hours. Semesters vary from one university to the next, but let's assume that there are 15 weeks in a semester. A 1-credit face-to-face course would require one hour of lecture ... plus two hours of additional study per week = 3 hours per week ... times 15 weeks = 45 hours per semester. A 2 credit hour course = 90 hours of online study, and a 3 credit hour course = 135 hours. These numbers should not be taken literally, but provide useful guides when comparing a series of packages of short online courses to on-campus face-to-face courses.


Robert: OK. To help me understand this conversion process, let's suppose an online package only contained two short courses. Suppose the first course lasted 4 weeks with an estimated 9 hours of study per week. This would mean 36 of hours of study for that course. Suppose the second course lasted 9 weeks with an estimated 6 hours of study each week. This would mean 54 hours of study for that course. Adding 36 + 54= 90 hours for the two courses. Now dividing by 45 hours per credit-hour = 90/45 = 2. All other things being equal, as economists are fond of saying, this means that I would learn about the same from these two short courses as I would from a 2 credit hour face-to-face course on campus.

Dr. B: Yes, but you should also note that most short online courses are self-paced. The total time to complete your two hypothetical courses would have been 4 + 9 = 13 weeks. But if you always studied 12 to 15 hours per week, you could finish these short courses in less than 13 weeks ... yet you would still only learn about 2 credit hours worth of new knowledge from the two courses in the package. 

Robert: OK, these credit hour conversions are tedious, but straight-forward. So here's my next question: How do I estimate the number of 3 credit courses that I would need to complete my pivot?

Dr. B: Here's two pieces of advice. First, I would examine university online catalogs. Look for courses that cover the subjects you think you need to learn for your pivot. There won't be much variation from one university to the next. So I anticipate that you will find the same number of 3 credit courses, more or less, wherever you look. 

Second, I think you should assume that things may take a bit more time and effort than you anticipate. Universities provide an array of support services for students in their on-campus courses. For example, you can ask professors questions in class. Professors (or their teaching assistants) grade each student's assignments, providing corrective comments tailored to each student's submissions. And professors have office hours during which students can obtain tutorials about topics they don't understand. When universities offer online programs, they try to provide equivalent support services via chatrooms, videoconferences, email, even telephone calls. If your non-degree short courses don't provide these supports, then "all other things" are not equal. So it might actually take more hours of study in your short courses to learn the same material.

Now stepping back from the pivot that you are currently considering, I would suggest that most professionals should expect that information technology will disrupt their careers more than once. Some will drastically alter their career paths by acquiring new degrees. Others who do not want to acquire new degrees will have to pivot their way through these disruptions again and again and again. The necessity for new degrees or pivots reflects a fundamental change in our society. It's no longer enough to be a lifelong learner; most professionals will have to become lifelong formal learners, by which I mean that they will have to enroll in formal programs of study from time to time throughout their careers. 

III. Providers of JOOPs

This note is merely an "introduction" so the following list does not include all of the important providers of JOOPs.  It only includes the four providers of courses that I myself completed or explored within the last three years.

A. Udacity

A for-profit company, Udacity was founded by Sebastian Thrun in 2012, the year of the "Big Bang" that produced the three brightest galaxies in the new universe of MOOCs: Udacity, edX, and Coursera. 

Udacity partners with some of the biggest technology companies in the world -- Facebook, Google, Amazon, AT&T, Nvidia, IBM, GitHub, and Didi -- to develop JOOPs that teach students the specific skills their corporate partners look for when hiring technical staff.  Udacity calls its job-oriented online programs "nanodegrees" which it describes as follows:

  • "Get Job Ready … Master in-demand skills. Build and design amazing projects. Earn a valued credential. Launch your career in Data Science, Machine Learning, Android, iOS, and more. Be in demand."
Udacity has been a pioneer in the development of JOOPs and associated support services. In my opinion, its current position with regards to JOOPs is comparable to Apple's position with regards to smartphones. For the first couple of years after Apple produced its first iPhone, the iPhone's features defined smartphones. It took a few years for other smartphone producers playing "catch up" to develop competitive products, and a few more years before they developed new features that Apple itself had to emulate in order to maintain its dominant position. At this point Udacity is the clear leader in JOOPs; other providers are playing "catch up" ... or not.

Thrun, a former tenured professor at Stanford University, offered the world's first MOOC in 2011 while he was a high level member of Google's technical staff. His course in artificial intelligence enrolled 160,000 students. When Thrun left Google to found Udacity, he partnered with some leading U.S. universities to produce MOOCs. Disappointed by the results of his partnerships with universities, Thrun made a famous "pivot" in 2014 in which he abandoned his academic partners (except Georgia Tech) and established new partnerships with leading corporations in order to produce nanodegrees. The names of the partners who were involved are identified on the Web pages of each nanodegree.  

B. DataCamp 
Founded in 2013 by Jonathan Cornelissen, DataCamp has headquarters in Belgium and Cambridge, MA. Its initial focus is "Data Science", so its JOOPs train "Data Scientists". However DataCamp is prepared to broaden its scope to include other fields at some point in the future. It calls its JOOPs "career tracks", described on its Website as follows:
  • "Our career tracks are hand-picked by industry experts. You will learn all you need to start a new career in the data science field."
The courses in its career tracks are based on the two most popular languages in the data science community: Python and R. 

Like Udacity, DataCamp works with partners in the corporate world in the development of its career tracks. But whereas Udacity calls the attention of prospective students to the eminence of its industry partners, DataCamp emphasizes the eminence of its instructors who are highly respected data scientists, e.g., Hadley Wickham -- whom some have hailed as a software "rock star". Full disclosure requires that I admit to being dazzled by Wickham's capacity to add such an impressive array of powerful tools to the R language that enable a R developers to create elegant applications whose output is readily understood by their clients. Wickham's involvement as a DataCamp instructor persuaded me to explore their courses. Unfortunately, DataCamp does not offer the kinds of support services provided by Udacity ... yet. 

  • Additional information about DataCamp can be found on its website, especially from the articles linked to its press page.
C. edX 
One of the Big Three providers of MOOCs, edX was founded in 2012 by M.I.T. and Harvard University. The edX consortium is a non-profit operation that currently includes 51 of the world's leading universities. Its courses are usually developed and taught by faculty from one of the consortium's member institutions.

edX currently offers JOOPs that it calls "Professional Certificate Programs" described on the programs' Web page as follows:

  • "Professional Certificate programs are series of courses designed by industry leaders and top universities to build and enhance critical professional skills needed to succeed in today's most in-demand fields. Find the program that meets your specific needs. Stand out and succeed at work."
This description suggests that edX academic members developed these programs in partnership with eminent corporate partners. Like DataCamp, edX does not offer an array of support services for its students ... yet. 


D. Coursera 
Like Udacity, Coursera is a for-profit organization that was founded by Stanford faculty in 2012. Like edX, Coursera's 2,209 courses are developed and taught by faculty from its 150 academic partners, all of whom are leading universities and other educational institutions. 

Coursera offers "specializations", i.e. programs that are typically composed of three to five MOOCs. But unlike edX, Coursera has not designated a subgroup of its programs as "job-oriented". Are all of its specializations job-oriented? No. Are any of its specializations job-oriented? Definitely, but I have difficulty identifying which ones are and which ones aren't -- with one exception:

  • Coursera's "Data Science" specialization is definitely a JOOP. How do I know? Because I myself completed the ten courses in this program, including its capstone project. 
     
  • Data Science is described on Coursera's Web pages as follows: "Launch Your Career in Data Science ... This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material." ==> This is the same kind of descriptive language used by Udacity, DataCamp, and edX for their JOOPs.
     
  • The Web page for this specialization also lists two industry partners -- Yelp and SwiftKey.

IV. Profiles of Programs
The following profiles summarize the programs offered by each provider, but include enough details to show that Udacity offers substantially more support for students in its JOOPs than the other providers and generally charges substantially higher tuition and other fees. Udacity seems to assume that potential students will understand that its more extensive support services funded by its higher tuition and fees will increase the likelihood that they will acquire the skills they need to find new jobs after they graduate.

How can we determine the involvement of industry partners in the development of JOOPs? I suggest that the acid test should be the public commitment of industry partners to hire the program's best graduates. Any partner who made this commitment would be heavily involved in the program's development in order to be sure that its graduates were the kind of professionals the partner really wanted to hire. On the other hand, programs that were developed without the benefit of extensive input from industry partners would be less likely to produce graduates who would be hired by anyone. Unfortunately, as the profiles will show, none of the four providers has obtained this kind of iron-clad commitment from any of its industry partners.

Finally, JOOPs are collections of short courses, shorter than the standard 3 credit 15 week semester courses with which most potential students are familiar.  The following profiles include rough estimates of the number of credit hours that would be equivalent to each short course as per the process described in the "conversation" between Dr. B. and his former student in Job-Oriented Courseloads (above). In other words, given the amount of study time required for a course in a JOOP, the profiles provide rough estimates of the number of credit hours the student would expect to earn if he or she invested the same amount of time in an on-campus course that was offered for credit: 
  • Readers will recall that a 1 credit hour face-to-face course = 45 hours student effort ... because 1 semester = 15 weeks, and students attend a 1 hour lecture per week + study 2 hours each week = 3 hours effort each week. Total effort per semester = 3 hours/week * 15 weeks =  45 hours per semester.
     
  • Given the total number of weeks in all the short courses in a package and the number of estimated hours of study required per week, weeks * hours/week = total hours of study for the package. Then divide total hours by 45 hours per credit hour = estimated credit hours.
     
  • If the lengths of the courses are given in months, first convert months to weeks by dividing months by 12 months per year * 52 weeks in a year = weeks in the course.
These rough estimates should be good enough to make plausible comparisons of the courses offered in JOOPs with the courses measured in credit hours offered by universities in their on-campus degree programs.

Apologies to the reader -- I have included the tedious step-by-step calculations of tuition and equivalent credit hours in the following profiles in order to make it easier for me to identify/correct any errors (and to update the estimates when the providers change the input values), and also to make it easier for readers to see how I derived these estimates. 


A. Udacity

Package Name -- "nanodegrees"

Number -- Udacity currently offers 16 nanodegrees

Levels -- Udacity's programs are classified as "beginner", "intermediate", and "advanced" 


Open vs. Closed -- Required backgrounds are suggested for "beginner" and "intermediate" programs, but they are open to anyone. "Machine Learning" is open, but the other "advanced" programs are closed ==> students apply for admission and are admitted on the basis of their qualifications.

Projects -- Students progress through the programs by completing projects, i..e, assignments  that are comparable to the real assignments that professionals in the students' intended field must deal with. 

    Programs, estimated hours of study time required, tuition for programs, partners (cites first 2 or 3 partners listed on Udacity's Web pages if there are more than one) ... and equivalent credit hours

    Self-paced MOOCs offered by Udacity provide the knowledge required to complete each project. Most of Udacity's online courses are open to anyone for free; but non-paying students do not have access to nanodegree projects. Some nano degrees estimate higher weekly study times for their courses than others, but all estimates lie between 8 and 12 hours per week. The higher estimate, 12 hours per week, is used for all estimates of equivalent credit hours in the following lists of programs:
    • Beginner 
      -- Digital Marketing (8 projects, 3 months, $999 -- Facebook, Google, Hootsuite) ... credits hours = (3 months / 12) * 52 weeks  * 12 hours per week / 45  = 3.5 credits
      -- Business Analyst (8 projects, 16 wks, $200/month, tuition = 16 weeks /(52 weeks/12  months)* $200 per month = $738 -- Alteryx, Tableau) ... credit hours = 16 weeks * 12 hours per week / 45 = 4.3
      -- Android Basics (10 projects, 6 mos, $199/month, tuition = 6 * $199 = $1,194 -- Google ... Note: This nanodegree is not a "JOOP" because it does not prepare students for a career change; it just prepares them to enroll in nanodegrees that are JOOPs ... credit hours = (6 months / 12) * 52 weeks * 12 hours per week / 45 = 6.9
      -- Intro to Programming (5 projects, 5 months, $399... Note: This nanodegree is not a "JOOP" because it does not prepare students for a career change; it just prepares them to enroll in nanodegrees that are JOOPs ... credit hours = (5 months / 12) * 52 weeks * 12 hours per week  / 45 = 5.8

    • Intermediate 
      -- React (3 projects, 4 months, $499 -- React Training) ... credit hours = (4 months/12 ) * 52 weeks * 12 / 45 = 4.6

      -- VR Developer (13 projects, 3 two-month terms, $400/term, tuition = 3 * $400 = $1,200 -- Google VR, Vive, Upload) ... credit hours =(2 * 3 months /12) * 52 weeks * 12 hours per week /45 = 6.9 
      -- Android Developer (7 projects, 9 months, $199/month, tuition 9 * $199 = $1,791 -- Google) ... credit hours = (9 months/12) * 52 weeks* 12 hours per week  45 = 10.4
      -- Front End Web Developer (7 projects, 6 months, $199/month, tuition = 6 * $199 = $1,194 -- AT&T, Google, GitHub) ... credit hours = (6 months /12) * 52 weeks * 12 hours per week /45 = 6.9 
      -- Full Stack Web Developer (7 projects, 6 months, $199/month, tuition = 6 * $199 = $1,194 -- Amazon, GitHub, AT&T)  ... credit hours = (6 months/ 12) * 52 * 12 / 45 = 6.9
      -- Data Analyst (7 projects, 260 hours, $199/month, tuition = (260 hours / 12 hours/week) / (52 weeks/12 months) * $199 per month= $1,990 -- Facebook, Tableau)  ... credit hours = 260 hours / 45 = 5.7
      -- iOS Developer (14 projects, 6 mos, $199/month, tuition = $1,194 -- AT&T, Lyft, Google) ... credit hours = (6 months/ 12) * 52 * 12 hours per week   45 = 6.9
      -- Deep Learning Foundations (5 projects, 6 months, $399 [obtained from Reddit])  ... Note: This nanodegree is not a "JOOP" because it does not prepare students for a career change; it just prepares students for & guarantees their admission into Udacity's Robotics, Self-Driving Car, and AI advanced nanodegree programs) ... credit hours = (6 months/12 * 52) * 12 hours per week /45 = 6.9

       
    • Advanced 
      Robotics (4 projects,  2 three-month terms, $1200 per term, tuition = 2 * $1200 = $2400 -- Bosch, Electric Movement, iRobot)  ... credit hours = (2 * 3 months / 12 ) * 52 * 12 hours per week / 45 = 6.9
      Artificial Intelligence (4 projects, 2 three-month terms, $800 per term, tuition = 2 * $800 = $1,600 -- IBM Watson, Amazon Alexa, DiDi) ... credit hours = (2 * 3 months / 12) * 52 * 12 hours per week / 45 = 6.9
      Self-Driving Car Engineer (5 "challenges", three 12-week terms, $800/term, tuition = 3 * $800 = $2400 -- Mercedes Benz, Nvidia, Uber ATG) ... credit hours = 3 terms * 12 weeks/term * 12 hours per week  / 45 = 9.6
      Machine Learning Engineer (11 projects,  $199/month, 6 months, tuition  = 6 * 199 = $1,194 -- Kaggle (acquired by Google)) ... credit hours = (6 months/12) * 52 * 12 hours per week / 45 = 6.9
    As the reader can see from the highlighted numbers at the end of each program line, Udacity expects its students to invest a substantial amount of time studying for the courses in its nanodegrees. Most of its courses require study time that would have earned at least 6.9 credits if the students were enrolled in degree programs. Indeed, students who prepare for its Robotics (6.9 credits), AI (6.9 credits), and Self-Driving Car Engineer (9.6 credits) programs by first taking its Deep Learning Foundations (6.9 credits) would have earned 13.8, 13.8, and 16.5 credits from degree programs from degree programs, i.e., four or five 3 credit courses.

    Industry Partners -- How involved were Udacity's partners in the development of its nanodegrees? None of its programs passed the "acid test" that I proposed earlier, i.e., none of its industry partners posted firm commitments on their nanodegree Web pages that they would hire the programs' best graduates. So I began with Sebastian Thrun's position as a former member of Google's senior technical staff, a position made him a certified member of Silicon Valley's technical elite, a status that facilitated his capacity to obtain well publicized support for Udacity's programs from Google and other leading firms in the Valley. Then I looked for other indicators of his parters' involvement, especially their reputations.
    • Google "owns" the Android OS and is deeply committed to virtual reality (VR) via its cardboard initiative. Therefore it seems likely that Google would closely scrutinize Udacity's Android and VR courses to be sure that they provided the required skill sets for Android and VR developers before adding its name as an industry partner for these three nanodegrees. 
       
    • Google recently purchased Kaggle, Udacity's industry partner for machine learning and the most prominent organizer of competitions for data science/machine learning experts. Therefore it seems likely that Google would closely scrutinize Udacity's machine learning engineer nanodegree to be sure that it provided graduates with the kinds of skills required to do well in Kaggles
       
    • Google and Facebook owe their massive success to their mastery of digital marketing and to advertisers' continuing faith in their mastery. It therefore seems likely that both companies would closely scrutinize Udacity's digital marketing nanodegree to ensure that this program would enhance their brands. 
       
    • IBM recently positioned its Watson AI system as the cornerstone for a wide array of new services that it will provide to businesses and governments in the near future. AI is a broad field, so it seems likely that IBM would have closely scrutinized Udacity's advanced AI nanodegree to be sure that its graduates acquired the particular skills required to appreciate potential applications of Watson's particular embodiment of AI technologies. 
       
    • And then there's the "pipeline" problem. Responding to pressure from the Rev. Jesse Jackson, Sr. and other activists a few years ago, the most prominent tech firms in Silicon Valley have released annual reports that document their continuing underemployment of female, Black, and Hispanic employees on their tech staffs. Their continuing "explanation" for their lack of diversity has been the low percentage of women, Black, and Hispanic students in their traditional pipelines, i.e, the colleges and universities from which they recruit most of their tech employees.  

      Udacity's nanodegrees provide their industry partners with new pipelines. Therefore it will be highly embarrassing to Google, Facebook, GitHub, and Udacity's other Silicon Valley partners if they decline to hire women, Black, and Hispanic graduates of Udacity's programs. So the best way for them to avoid this debacle is to continuously audit Udacity's programs to be sure that the programs are teaching the skills the partners are really hiring.
    Support staff are experienced experts who answer students' questions, evaluate their projects, and act as mentors. 

    50% tuition refunds are awarded to students who complete the Android Basics, Android Developer, Data Analyst, Front End Developer, Full Stack Web Developer, Become an iOS Developer, and Machine Learning programs in 12 months.

    Face-to-face weekly meetings are open to students who subscribe to the "Udacity Connect" service. During these sessions students can discuss their courses and projects with staff and other students, and enhance their professional networks. At this time the UConnect service is only available in San Francisco, Los Angeles, and New York. UConnect costs $99 per month.

    Job Guarantees are provided to students who subscribe to Udacity's "Nanodegree Plus" service. Udacity's slogan for this service is 
    "Get a job or your money back". Subscribers receive help finding jobs in their career tracks within 6 months after graduation and receive 100% refunds of their paid tuition if they don't find jobs. The detailed "Terms and Conditions" for this service should leave no doubt that Udacity expects students to invest substantial time and effort to earn Udacity's money back guarantee.  At the present time this service is only available for the following nanodegrees: Machine Learning Engineer, Full Stack Web Developer, Android Developer, Become an iOS Developer, and Data Analyst. As noted on Thrun's blog, the Nanodegree Plus service costs $299 per month, but this subscription fee includes tuition.
    B. DataCamp

    Package Name -- "Career Tracks"

    Number -- DataCamp currently offers 7 career tracks

    Open vs. Closed -- All courses and tracks are open to all students.


    Programs, estimated hours of study time required, tuition for programs ... and equivalent credit hours

    • DataCamp students pay $29 per month subscription fees for access to all DataCamp courses. The fee per week = 29 /(52 weeks/12 months) = $6.70
    • The following list assumes that serious students will invest at least 12 hours per week in their self-paced courses, the same as was used for Udacity's profile (above)
    DataCamp's short lecture videos are usually accompanied by online labs in which students write scripts and functions to perform the calculations discussed in the short videos. DataCamp provides is own estimates of the time students should expect to view the videos and complete the labs. 

    My own experience in a few DataCamp's courses was that mastery of the content of the videos plus labs required that I also spend substantial additional time playing around with similar problems in the IDE on my own computer (R Studio) in order to be sure I could write comparable scripts and programs outside of the browser-based IDE provided by DataCamp. How much additional time? 

    Rather than provide estimated times based on my personal experience, I think it's better to reframe DataCamp's videos + labs as an example of a teaching style that some instructors in traditional face-to-face degree courses have used. Following John Dewey's classic maxim -- "Learn by doing" -- these instructors spend class time making brief presentations of concepts and techniques. Then they engage their students in hands-on applications of these ideas for the remainder of the class. Homework and other outside class activities provide opportunities for students to deepen their understanding of what they learned in class. 

    Accordingly, in the following list of programs I interpret DataCamp's estimates as "lecture" time, then add twice that time, as usual, to obtain rough estimates of the total time students spend on their courses, i.e., total time = 3 * lecture time.
    • R Developer (10 courses) ... total hours = 3 * 40 DC estimate = 120 hours ... weeks = 120 hours / 12 hours per week = 10 weeks ... tuition = 10 * $6.70/week = $67 ... credit hours = 120 hours / 45 = 2.6
    • Data Analyst with R (16 courses) ... total hours = 3 * 64 DC estimate = 192 hours ... weeks = 192 hours / 12 hours per week = 16 weeks ... tuition = 16 * $6.70/week = $107... credit hours = 192 hours/ 45 = 4.3 credits
    • Data Scientist with R (23 courses) ... total hours = 3 * 95 DC estimate = 285 hours ... weeks = 285 / 12 = 23.75 ... tuition = 23.75 * $6.70 = $159 ... credit hours = 285 / 45  = 6.3
    • Quantitative Analyst with R (12 courses) ... total hours  = 3 * 51 DC estimate = 153 ... weeks = 153 / 12 hours per week = 12.75 ... tuition = 12.75 * $6.70 = $85 ... credit = 153/ 45 = 3.4 
    • Python Developer (10 courses) ... total hours = 3 * 36 DC estimate = 108 ... weeks = 108 / 12 = 9 ... tuition =9 * $6.70 = $63 ... credit hours = 108 / 45 = 2.4 
    • Data Analyst with Python (13 courses) ... total hours = 3 * 47 DC estimate = 141 ... weeks = 141 / 12 hours per week = 11.75 ... tuition = 11.75 * $6.70 = $79 ... credits =  141 / 45 = 3.1
    • Data Scientist with Python (20 courses) ... total hours = 3 * 67 DC estimate = 201 ... weeks = 201 / 12 hours per week = 16.75 = $112 ... tuition = 16.75 * $6.70 ... credit hours= 201 / 45 = 4.5
    "Industry partners" -- Whereas Udacity and edX reference the reputations of prominent corporate partners, DataCamp references the eminence of its instructors. Its students learn new skills from instructors who are renowned practitioners of those skills in various industries. If I modified my acid test for DataCamp to require that its instructors commit to writing strong letters of recommendation for its best graduates, the programs would still not pass my test because their Web pages offer no commitments from the instructors to helping their best grads find employment.
    C. edX

    Package name -- "Professional Certificate Programs"

    Number -- edX currently offers 18 Professional Certificate Programs  

    Levels -- edX courses are classified as "beginner", "intermediate", and "advanced"

    Open vs. closed -- All certificate programs are open to all students.


    Programs, estimated hours of study time required, tuition for programs ... and equivalent credit hours
    Note 1  -- Tuition is the price students pay for obtaining verified certificates that they passed the courses in each program; students who don't want a verified certificate can take the courses for free.

    Note 2 -- Many edX programs suggest a range of study hours per week, e.g., 3 to 4; when calculating the study times required for all of the courses in a program, I consistently used the upper end of the study range for each course in the program.

    • Introductory Programs 
      -- Inclusive Leadership (4 intro courses) ... total hours =  4*1.5 + 4*1.5 + 4*2 + 1*1 = 21 hours, tuition = 50 + 50 +50 + 25 = $175) ... credit hours = 21 / 45 = 0.50.5
      -- Data Science for Executives (3 intro courses) ... total hours = 5*10 + 5*10 + 5*10 = 150 hours, tuition+ 99 + 99 + 149 = $347... credit hours = 150 / 45 = 3.3
      -- Java and Android Foundation (3 intro courses) ... total hours = 5*5 + 5*5 + 6*5 = 80 hours, tuition= 99 + 99 + 99 = $297) ... credit hours = 80/45 = 1.8
      -- Gestion Publica para el Desarrollo (3 intro courses) ... total hours = 6*6 + 5*6 + 7*7 = 135 hours, 25 + 25 + 25 = $75) ... credit hours = 135 / 45 = 3.0
      -- Project Finance and Public Private Partnerships (7 intro courses) ... total hours = 6 * 3*2 + 2 = 38 hours, tuition = 99 + 189 + 189 + 189 + 189 + 189 + 355 = $1399) ... credit hours = 38 / 45 = 0.8
      -- Essentials of Cybersecurity (4 intro courses) ... total hours = 4 * 4*5 = 80 hours, 79 + 79 + 79 + 79 = $316) ... credit hours = 80 / 45 = 1.8
      -- Introduction to Java Programming (3 intro courses) ... total hours =  5*10 + 5*7 + 5*7  = 120 hours, 99 + 99 + 99 = $297) ... credit hours = 120 / 45 = 2.7
      -- Six Sigma and Lean: Quantitative Tools for Quality and Productivity (3 intro courses) ... time =  8*4 + 8*4 + 8*4= 96 hours, 88 + 88 + 88 = $264 ... credit hours = 96 / 45 = 2.1
    • Intermediate Programs 
      -- Data Science (9 courses = 2 intro + 6 inter + 1 adv ) + capstone [adv] -- Microsoft) ... total hours = 6*4 + 6*5 + 6*4 + 6*4 + 4*2 + 6*4 + 6*4 +6*8 + 4*4 + 4*4 = 238 hours, 10 * 99 = $990 ) ... credit hours = 238 / 45 = 5.3
      -- Computer Science Essentials for Software Development (4 inter courses) ... total hours = 4*8 * 4 = 128 hours, 149 + 149 + 149 + 149 = $596)  ... credit hours = 128 / 45 = 2.8
      -- Front-End Web Developer (5 courses = 3 intro + 1 inter + 2 adv) ... total hours = 5*8 + 6*6 + 6*8 + 5*8 + 4*8 = 196 hours, 129 + 129 + 99 + 49 + 99 = $505) ... credit hours = 196 / 45 = 4.3
      -- Virtual Reality App Development (3 courses = 1 intro + 2 inter) ... total hours = 6*7 + 6*7 + 6*7 = 112 hours,  99 + 99 + 99 = $297) ... credit hours = 112 / 45 = 2.5
      -- Retail and Omnichannel Management (2 inter courses) ... time = 4*4 + 4*4 = 32 hours, 99 + 99 = $198) ... credit hours = 32 / 45 = 0.7
      -- Mergers and Acquisitions (M&A) (6 courses = 5 int + 1 adv) ... total hours =   5*4*2 + 1 = 41 hours,  50 + 100 + 200 + 300 + 400 + 500 = $1550) ... credit hours = 41 / 45 = 0.9
      -- Digital Marketing (4 inter courses) ... total hours = 6*4 + 6*3 + 6*4 + 6*3 = 84 hours, 585 + 585 + 585 + 585 = $2340) ... credit hours = 84 / 45 =  1.9
      -- Risk Management (6 inter courses) ... total hours = 5*4*2 + 1= 41 hours, 99 + 249 + 349 + 349 + 349 + 500 = $1895) ... credit hours = 0.9
      -- Agile Development Using Ruby on Rails (2 inter courses) ... total hours = 6*12 + 6*12 = 192 hours, 99 + 99 = $198) ... credit hours = 192 / 45 = 4.3
      -- Mortgage Backed Securities (MBS) (3 inter courses) ... total hours = 2*4 + 2*4 + 2 = 18 hours, 450 + 550 + 399 = $1399) ... credit hours =  18 / 45 = 0.4
    Industry Partners -- Although the description of the edX Professional Certificate Programs quoted in Part II of this note declared that "industry leaders" were involved in the development of these programs, only one program provided tangible indication of such involvement -- the Data Science program that is taught by Microsoft, instead of by an edX academic partner. By contrast, the partners for the other edX programs are only cited as sources of favorable comments about the programs, comments that read more like snippets from favorable book reviews than as commitments by the partners to hiring the program's best graduates.

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    D. Coursera

    Package Name -- "Specializations"

    Number -- For the reasons that I noted in Providers section, I can't determine the number of JOOPs offered by Coursera. The Data Science program offered by professors from Johns Hopkins University is definitely a JOOP, but Coursera does not identify which of its other programs are job-oriented. 

    Open vs. Closed -- Required backgrounds are suggested for all courses in all specializations, but all courses and specializations are open to all students.


    Programs, estimated hours of study time required, tuition for programs ... and equivalent credit hours
    • Data Science (9 courses + capstone) ... total hours = 1 course * 5w * 4h/w + 8 courses * 5w * 9h/w + 1 course * 8w * 9h/w = 452 hours, weeks= 5w + 8 * 5w + 8w = 53 weeks, tuition = 53 /52 * 12 =  12.2 months @ $49/mo = $593 ... Industry partners = Yelp and SwiftKey ... credit hours = 452 hours/ 45 hours =  10.0

    V. Conclusions

    When I decided to write this note, I did not anticipate coming to any "conclusions". I just wanted to provide detailed descriptions of the programs offered by a few prominent providers of JOOPs. Having recently retired from a long career as a member of the tenured faculty and administrative staff of a prominent university, I had decades of hands-on experience dealing with the nuts and bolts of programs in higher ed. So I knew what to notice when I looked under the hoods of these new job-oriented operations. 

    My decision to enroll in a job-oriented program as part of my personal effort to make a final career change meant that I could not claim to be a disinterested observer.  But I would argue that my status as a participant-observer gave me a keener appreciation of the limits of what these programs could or could not achieve. So that's what my conclusions are all about -- the limits of JOOPs, i.e., what I think they can and can't do for professionals looking to change their career paths.
    • Assessment
      As a retired professor and a current student, my biggest concern about JOOPs is assessment. In face-to-face and online courses offered for credit  by accredited institutions, the size of enrollments in course sections is limited so that there are enough faculty or teams of faculty plus teaching assistants to assess every student's submissions. While multiple choice questions and other types of closed assignments can be graded by software, human assessment is required for open-ended assignments like essays, reports, and projects -- especially in programs that provide professional training.

      Courses in Masters degree programs and other traditional gateways to various professions are often taught by part-time instructors who are practicing professionals so that students can obtain the benefits of expert opinions with regards to current best practices in the field. Peer evaluations from other students are useful, but they are insufficient substitutes for expert evaluations. Indeed, many masters degree programs include internships, practicums, and other field assignments wherein students work under the direct supervision of practicing professionals. 

      Question: How can JOOPs that do not provide expert assessments of realistic assignments enable students to acquire professional level skills in a field?

      My answer: I doubt that most students can attain professional level skills without the benefit of constructive critiques of their projects from experienced mentors.
       
    • Jumps vs. Pivots
      OK, let's trot out the mantra: "Jump with degrees; pivot with JOOPs." Now let's try that again in English ... :-)
       
      In times past, degrees provided entry into a wide range of professions. For example, MBAs provided entry into management; LLBs opened doors to legal careers; PhDs were required for academic positions and/or research; bachelors degrees became the minimum requirements for entry into an increasing number of non-specialized white collar occupations. If someone wanted to jump into a new field, they usually had to obtain another degree. 

      JOOPs can now be used by professionals who only want to "pivot", i.e. to change directions, but stay in the same field. Why pivot? Many reasons come to mind, but an increasing number of professionals in an increasing number of fields face slower career advances and/or loss of employment as result of the disruptive impact of information technology.  

      Professionals who want to pivot might only need to enhance their skills to include some computer-based methods that could be applied to old problems and/or address new problems that were inaccessible to their old skills. New skills might be acquired through relatively inexpensive JOOPs that were roughly equivalent to, say, 12 credits of new knowledge, rather than the expensive 48 or more credits for a Masters degree. 

      But how does a student know that he or she has learned their new skills well enough to find new employment? This brings me back to my primary concern -- assessment. In my own case, I did well in all of the courses I took in a JOOP; but all of my projects were assessed by other students; none were assessed by faculty or by practicing professionals. I passed ten courses and earned ten certificates ... but did I really pivot??? No one has ever accused me of being shy. Nevertheless, I didn't feel my usual confidence that I had learned my new skills well enough to meet the expectations of potential clients. So I did what conscientious students usually do when they don't think they have learned enough ==> I enrolled in more job-oriented courses ... :-(
       
    • Job search
      Colleges and universities have a long history of supporting the efforts of their degree graduates to find jobs. Letters of recommendation from faculty for their best students are probably the most widespread forms of this support. But many institutions host "Job Fairs" that enable recruiters from corporations and government agencies to conduct on-campus interviews with large numbers of students. And many institutions have established "Career Centers" wherein students can receive guidance on a wide range "Do's and Don'ts", including how to prepare more effective resumes, how to organize portfolios of their projects and other course submissions, and how to answer questions during job interviews. Taken together these traditional supports for the graduates of degree programs provide a useful reference model for the kinds of services that might be offered by the providers of JOOPs for their graduates.

      Whereas academic institutions rightly claim that obtaining jobs is just one of the many benefits that graduates of their degree programs derive from their education, jobs are the only benefits that graduates of JOOPs expect to receive.  Indeed, their students' success in obtaining jobs is the raison d'être for JOOPs and the acid test of their effectiveness. That's why I think that support for job search should be a mandatory component of all JOOPs. Of course, providers of JOOPs won't have the funds to pay for these services if their tuition is too low.
       
    • Data vs. Anecdotes
      In my opinion none of the providers of JOOPs discussed in this note have proven their effectiveness as enablers of career change. Their Websites contain glowing anecdotal testimonies from their industry partners and from their graduates, but none of the providers offers systematic data about their enrollments, graduations, time-to-completions, gainful employment after graduation, and the number of graduates who were hired by industry partners; nor do they identify which kinds of students have been the most/least successful in completing their programs. To be more specific, how are Black, Hispanic, and female students doing in their programs?

      These caveats notwithstanding, I hope that the details that I provided in the Profiles section of this note leave no doubt in the reader's mind that Udacity is far ahead of the other three providers in its efforts to address the limitations that I identified in my other conclusions. Udacity's experts assess students' assignments; it offers pivotable programs worth two to four 3 credit hour courses; and it provides vigorous support for its graduates' job search.  Furthermore, Udacity has more industry partners than the other providers; it displays more testimonials from satisfied students on its Web pages; and market-savy investors have seen enough promise in its business plans to pay prices for its stock that are high enough for Udacity to be valued at $1 billion dollars, making it the first "unicorn" in the MOOC universe. Nevertheless, Udacity can't prove that its programs are effective ... yet.

      A few years ago, coding bootcamps that showed a similar kind of early promise burst on the scene; but two of the most prominent bootcamps (Dev Bootcamp and Iron Yard) are folding -- reminders that early promise does not guarantee future success. If Udacity fails, it might be due to unforeseen flaws in its business plans. For example, some of the most talented students might find that the higher tuition and fees that Udacity charges in order to fund its support services were not worth the greater benefits that these services provided. A particularly interesting possibility is that DataCamp (or some other low cost /no frills provider) might disrupt Udacity's dominant position by adding just enough support services to entice substantial numbers of the most ambitious/talented students away from Udacity, students who wouldn't need as much support as most students. This loss would jeopardize Udacity's capacity to deliver the kind of top-rated students its partners most wanted to hire and would thereby weaken Udacity's partnerships.

      I also have reservations about a few of Udacity's current nanodegrees. Most nanodegrees facilitate pivots. For example, a developer who currently works on personal computers or mainframes might use the iOS Developer or Android developer nanodegrees to pivot to developing mobile apps for iPhones or Android phones. Or a JavaScript developer might execute an easy pivot via the React nanodegree, whose projects and courses would add Facebook's important React JavaScript library to the developer's toolkit. But I am skeptical that substantial numbers of non-PhDs in computer science will be able to pivot their way onto the high ground of AI/machine learning currently dominated by computer science PhDs from the best universities in the world. Some career changes still require full jumps, i.e., additional degrees, because they require more additional knowledge than can be gained through pivots. 

      For the foreseeable future, nanodegrees might pose riskier options for career changers than degree programs. But for those who only want to pivot rather than jump, the desired payoff may be worth the greater risk. As Bret Maverick, one of the twentieth century's most esteemed existential philosophers, was fond of saying: "Faint heart never filled a flush." ... :-)
    Full disclosure #2 ... Yes, I am seriously thinking about enrolling in one of Udacity's nanodegree programs ... :-)

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