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(There is no a priori reason to expect that we must be able to do anything to change student dropout and retention: hence the importance of direct, proven successes. Strategies based on improving it might turn out to be like reasoning that if you win the lottery jackpot with your first ticket then your money troubles will be over, or that if you invent a perpetual motion machine then you'll never need to worry about fuel bills again: the logic is correct, but there is no evidence that this is a practical, possible plan of action.)
Institutional dropout rates vary enormously within a given country (about 1% - 38% in the UK), and the most obvious difference between HEIs is their selectivity. The UK Open University (not usually included in these comparisons) has an even bigger dropout rate of 50%, and essentially does not select its student intake at all. We are unlikely to see any other intervention with anything like such a big effect on dropout as pre-selection.
While the most obvious selectivity is by prior academic achievement (e.g. high A-level scores), it could be that important parts of the selectivity (for achieving low dropout) is actually for pre-attunement to HE. If a student's parents both went to university, preferably the same university; if their school assumed they would go and pre-trained them e.g. to take notes, use the library, to write essays exhibiting critical thinking, etc., then this may make that student more likely to succeed. Furthermore there are associations, almost certainly causal, between wealth and family support on the one hand, and retention on the other. More accurately, different families demonstrate different amounts of commitment to keeping a student in education. Previous academic achievement is a measure of this because it measures their demonstrated commitment to date, and so selecting for achievement is also likely to select for continued support, and against students who may have to leave to support their families which is a common cause of dropout.
This kind of advantage may further extend to the built-in dropout-saving mechanisms within HEIs. A leading cause of dropout, particularly at the more successful HEIs, is mismatch between student and course or subject. Many more students "fix" this by changing courses. Although tough definitions would view this as dropout if it takes an extra year, other definitions and most students themselves do not. However the capacity to change courses and then succeed will be greater the more successful a student is at learning, and the more subjects they have taken earlier (e.g. at A-level) and successfully. Again, pre-selecting for the most successful students is likely to mean they are better able to take advantage of changing courses to avoid dropout.
Related to this is that there is a tradeoff for HEIs between dropout and widening participation. An HEI will usually do better at one, if they do worse at the other. This is rather starkly illustrated by the 2006 HESA figures, as reported by THES on 20 July 2007 p.6-7. The six bottom HEIs at participation are all in the top 10 HEIs at retention (low dropout), while their relationship with the top income for research is much weaker: only 2 of these 6 are also in the top 10 for research returns.
"I am not impressed by the Ivy League establishments. Of course they graduate the best: it's all they take, leaving to others the problem of educating the country. They will give you an education the way the banks will give you money, provided you can prove to their satisfaction that you don't need it." ( Peter De Vries)
What did he do? He redesigned his course to use a method of teaching and learning which Hake called "Interactive Engagement", and Mazur calls "Peer Instruction". Basically a feature is setting brain teazer questions based on key concepts known to be difficult for students, and using them to provoke peer discussion. (Nowadays this is done using EVS: Electronic Voting Systems.) Jim Boyle's methods are described in some detail, with collected evaluation evidence, in:
Could they be generalised to other subjects, and how? This is more speculative. EVS have been applied widely in many ways, of which the Mazur method is only one. The Mazur method really derives from Piaget, and indeed Cardinal Newman argued that peer discussion is more important to university education quality than professors or exams are. However would this always improve dropout rates?
My own guesses would be that the first thing is to look at what the bottleneck to achieving learning is in a particular subject: in basic Newtonian mechanics, a long educational literature shows that truly internalising the meaning of the concepts is problematic for many, perhaps most, students. Jim Boyle's redesign was on the basis of this literature i.e. it was addressing what was established as the main issue in learning that particular subject. So the generalisation of that would be to identify what the main bottleneck to success is in the subject under consideration, and address that. In other words, next to selecting students as likely to succeed anyway, supporting their effective learning of their particular subject may be the most effective type of intervention to improve retention that we could make.
My other guess at a generalisation would be that engaging students academically in their subject is of core importance: giving them the (justified) feeling of understanding regardless of how much this impacts on their test scores.
Tone and content: e.g. "I understand you missed the last tutorial and we're concerned: I wonder if there is anything we could do to help?" (as opposed to "What is your excuse for missing it?"). Or actually: "One of your instructors is concerned about your absences from his class at such an early time in the semester. Understand that instructors have different criteria for what they deem excessive, which might be far different from your own ideas. I tell you this only to notify you that your instructors do in fact notice when you attend or fail to attend their classes. If you are in need of any type of assistance, whether it be academic or personal, please feel free to contact an advisor in the Academic Support Center located at 22 Road Street (123 4567) or the staff at the University Counseling Center at the V.B. Harrison Building (123 4567). Information regarding Academic Probation, Dismissal and Suspension can be found at in the Undergraduate Catalogue."
In the first trial, about 40% of the class qualified by their absences for the intervention. Of these 87% of those getting the intervention got grade C or better, while only 55% of the control group did. In the second trial (with no control group) only 58% got a C or better: as if there were no effect. In the third trial, 70% got C or better. However that was in the second semester, when perhaps most of the dropouts had already occurred and the remaining students were much less likely to fail. Differences between the definite success of the first trial, and the possible failure of the others include:
There were big differences in the effectiveness of the two methods in reaching the students and gaining an acknowledgement. There was no sign (in an extensive survey) of any problems in the phone calls being seen as intrusive or unwelcome.
|Email group||Telephone group|
|Total no. of students meeting the "trigger"||30||30|
|No. of students who were definitely reached||5||20|
|Of these, no. who had already dropped out||2||5|
|Total no. of dropouts by end of semester||17||17|
It seems to me there are 3 conclusions we may draw from this.
|Year||Total students in trial||Increase in retention rates: experimental vs. control group|
Simpson,O. (2008) "Motivating learners in open and distance learning: do we need a new theory of learner support?" Open Learning: the journal of open and distance learning vol.23 no.3 pp.159-170
Finally, we should today (2007) consider other media than phones.
According to rumour at least, one academic at Hull chases up missing students
on Facebook to good effect. Other studies report on using SMS texting.
Dave Harley, Sandra Winn, Sarah Pemberton & Paula Wilcox (2007) "Using texting to support students' transition to university" Innovations in Education and Teaching International Vol.44 No.3 pp.229-241
The idea is to tackle the "no-show" students, who receive an unconditional offer of a place on a course, but never show up; in effect "pre-dropouts". The idea is to send monthly e-newsletters, welcoming the students, telling them a bit about what to do when they arrive, who the key people on the staff are, etc. Web page describing this Longer report.
The evidence is a year on year change when the e-newsletters were introduced: the no-shows (pre-dropouts) fell from 14 to 3 in the year in question (8.8% to 1.9%).
However I have now heard of a dramatically successful scheme in the psychology department at Edith Cowan university (in Perth, Western Australia), that has a scheme that has reduced dropout from about 23% to 5%. Further details here.
Trotter, E. and Roberts, C.A. (2006) "Enhancing the Early Student Experience" Higher Education Research and Development Vol.25 No.4 pp.371-386
This evidence is not from a controlled experiment, but from a natural one: analysing two existing courses. Trotter's research idea was to select two courses that were matched i.e. broadly comparable in discipline area, size, etc. except for markedly different retention rates, and then do in depth interviews etc. to discover what factors might be responsible. The most obvious of these, it seems at least to me, was that the low-dropout course used the first week for group projects, while the other offered more traditional induction activities such as a tour of the surrounding city. With hindsight, at least, we can recognise that spending the first week on group projects implicitly covers social integration (getting to know other students well), academic integration (getting to know one staff member well), in the context of an "authentic" task i.e. a task to do both with learning and the course (as opposed to, say, library induction tours, lectures on introductory topics that have low apparent connection with the profession and practice the course is meant to train students for).
Draper, S.W. & Cutts,Q. (2006) " Targeted remediation for a computer programming course using student facilitators" Practice and Evidence of the Scholarship of Teaching and Learning in Higher Education" vol.1 no.2 pp.117-128.
We have also just achieved such an effect ourselves on the first year programming course. The statistical effect size was about 0.5; and the difference in the means (the increase in exam marks) about half a grade point i.e. substantial.
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