I have a much simpler method to test inclination top programming, although it needs to be standardised. Nevertheless it is worth a try with programmers with proven inclination and a control group. It is a joke: Tell them or show them this:
A vet falls ill. he goes to see his family doctor. Vet: Hi Joe: GP: Hi Alan. What's the matter with you? Vet: you figure out. Regards, Ferenc "Music can't exist without notes and intervals. Conversation is the same. "Shut up and listen" has always been good advice to follow" Geoffrey Hamilton, Ph.D.(hon) ----- Original Message ---- > From: Alan Blackwell <alan.blackw...@cl.cam.ac.uk> > To: Stefano Federici <sfeder...@unica.it> > Cc: Richard O'Keefe <o...@cs.otago.ac.nz>; Thomas Green > <green...@ntlworld.com>; >PPIG Listserve <ppig-discuss-list@open.ac.uk>; alan.blackw...@cl.cam.ac.uk > Sent: Monday, 21 March, 2011 7:59:15 > Subject: Re: URGENT: Testing Inclination to Programming > > I may have missed it, but I don't think I saw a reference to the > series of studies by Beckwith and Burnett on self-efficacy as a > significant factor leading to gender differences in early > programming experiences. > > If your experimental population includes a mix of males and > females, you may find that this is a significant effect. I would > strongly recommend recruiting balanced numbers of males and > females, and carrying out analyses that consider interaction of > self-efficacy and gender. > > A typical study in this area, which shows *opposite* effects of > an experimental intervention for males and females, is this one: > http://portal.acm.org/citation.cfm?doid=1124772.1124808 > > (Perhaps needless to say to you, but for the benefit of other > readers - if you carry out an experiment in which the > manipulation has opposite effects for two halves of the sample, > and don't take this into account during analysis, the overall > result will be highly inconclusive, resulting in large variance > and small mean difference). > > Alan > > > Dear All, > > I went through one of the suggested papers about self-efficacy > > (Self-efficacy and mental models in learning to program, Ramalingam et > > al, 2004). Unfortunately I'm at present totally unable to understand > > the final results (path analysis of the model): > > > > post Self-Efficacy (R2 = .44) ==23*==> Performance - Grade (R2 = .30) > > Mental Model (R2 = .05) ==.40*==> Performance - Grade (R2 = .30) > > > > The paper says that "both what student know, as represented by their > > internal mental model, and what they believe about themselves, as > > represented by their self-efficacy, affect their performance in the > > course." > > > > Is there a naive way of rephrasing the 23* and .40* weights on the > > arrows from "post Self-Efficacy" to "Performance - Grade" and from > > "Mental Model" to "Performance - Grade"? I mean, in terms of > > percentages, meaningfulness or other. > > > > Thanks in advance for all the help you keep giving me > > > > Stefano > > > > > > > > Stefano Federici > > ------------------------------------------------- > > Università degli Studi di Cagliari > > Facoltà di Scienze della Formazione > > Dipartimento di Scienze Pedagogiche e Filosofiche > > Via Is Mirrionis 1, 09123 Cagliari, Italia > > ------------------------------------------------- > > Cell: +39 349 818 1955 Tel.: +39 070 675 7815 > > Fax: +39 070 675 7113 > > > > > > > > -- > > The Open University is incorporated by Royal Charter (RC 000391), an exempt >charity in England & Wales and a charity registered in Scotland (SC 038302). > > > > > > -- > Alan Blackwell > Reader in Interdisciplinary Design, University of Cambridge > Further details from www.cl.cam.ac.uk/~afb21/ > >
