Alcohol advertising in sport and non-sport TV in Australia, during children's viewing times

Estimate the amount of alcohol advertising in sport vs. non-sport programming in Australian free-to-air TV and identify children's viewing audience composition at different times of the day. Alcohol advertising and TV viewing audience data were purchased for free-to-air sport and non-sport TV in Australia for 2012. We counted alcohol advertisements in sport and non-sport TV in daytime (6 am-8.29 pm) and evening periods (8.30 pm-11.59 pm) and estimated viewing audiences for children and young adults (0-4 years, 5-13 years, 14-17 years, 18-29 years). During the daytime, most of the alcohol advertising (87%) was on sport TV. In the evening, most alcohol advertising (86%) was in non-sport TV. There was little difference in the mean number of children (0-17 years) viewing TV in the evening (N = 273,989), compared with the daytime (N = 235,233). In programs containing alcohol advertising, sport TV had a greater mean number of alcohol adverts per hour (mean 1.74, SD = 1.1) than non-sport TV (mean 1.35, SD = .94). Alcohol advertising during the daytime, when large numbers of children are watching TV, is predominantly in free-to-air sport TV. By permitting day-time advertising in sport programs and in any programs from 8.30 pm when many children are still watching TV, current regulations are not protecting children from exposure to alcohol advertising.

Losing their marbles : syntax-free programming for assessing problem-solving skills

Novice programmers have difficulty developing an algorithmic solution while simultaneously obeying the syntactic constraints of the target programming language. To see how students fare in algorithmic problem solving when not burdened by syntax, we conducted an experiment in which a large class of beginning programmers were required to write a solution to a computational problem in structured English, as if instructing a child, without reference to program code at all. The students produced an unexpectedly wide range of correct, and attempted, solutions, some of which had not occurred to their teachers. We also found that many common programming errors were evident in the natural language algorithms, including failure to ensure loop termination, hardwiring of solutions, failure to properly initialise the computation, and use of unnecessary temporary variables, suggesting that these mistakes are caused by inexperience at thinking algorithmically, rather than difficulties in expressing solutions as program code.