A Mixed-Methods Study of Novice Programmer Interaction with Python Error Messages
The ability to interpret error messages in order to find and fix bugs is an essential skill for novice programmers. Unfortunately, the technical language of most error messages can hinder the progress of CS1 students and can lead to feelings of confusion and frustration. A potential intervention for CS educators is the use of enhanced error messages that utilise natural-language geared towards novice learners, but the current discourse in CS Education regarding benefits of such messages is inconclusive. In this paper, we describe a planned, semi-controlled experiment running parallel to a CS1 course at the University of Toronto Scarborough. The study aims to build upon existing work in quantifying the effects of enhanced error messages by incorporating additional quantitative metrics, usability surveys, student feedback, and semi-structured interviews. The additional methods serve to measure not only the effects on error recovery, but student satisfaction, sense of frustration and overall attitude towards error messages and debugging.
Hedy: A Gradual Language for Programming Education
One of the aspects of programming that learners often struggle with is the syntax of programming languages: remembering the right commands to use and combining those into a working program. Prior research demonstrated that students submit source code with syntax errors in 73% of cases and even the best students do so in 50% of cases. An analysis of 37 million compilations by 250.000 students found that the most common error was a syntax error, which occurred in almost 800.000 compilations. It was also found that Java and Perl are not easier to understand than a programming language with randomly generated keywords, stressing the difficulties that novices face in understanding syntax. This paper presents Hedy: a new way of teaching the syntax of a programming language to novices, inspired by educational methods by which punctuation is taught to children. Hedy starts as a simple programming language without any syntactic elements such as brackets, colons or indentation. The rules slowly and gradually change until the novices are programming in Python. Hedy is evaluated on 9714 programs.
Intentional poisoning cases of animals with anticholinesterase pesticide-carbofuran in Sri Lanka.
Carbofuran is a broad spectrum insecticide and nematicide which inhibits acetyl cholinesterase. Several intentional poisoning cases of animals and birds including crows, dogs, cow, and elephant, using carbofuran were reported in Sri Lanka. Qualitative analysis of carbofuran in biological specimens was carried out using T.L.C and GC-MS. The quantitative analysis was carried out by HPLC using Zorbax Eclips XDB-C18 (150 x 4.6 mm I.D x 5 microm particle size) column with acetonitrile: water 25:75 v/v mobile phase and UV detection at 210 nm. The liquid-liquid extraction with chloroform was reproducible and sensitive. The procedure was validated in terms of linearity (0.996<r<0.999) for concentrations ranging from 1 to 200 microg/ml, repeatability (RSD 4.4% at 100 microg/ml, n=10) extraction recovery (91.7% at 100 microg/g, 77.3% at 20 microg/g), limit of detection (S/N ratio=3, 0.7 microg/ml) and limit of quantification (S/N ratio=10, 2.4 microg/ml). The method was found satisfactory and successfully applied in fatal cases of animals and birds due to carbofuran poisoning. The fatal carbofuran levels detected were in the range of 42-910 microg/g in crow's gizzard and contents, 50-800 microg/g in dog's stomach contents, 13-20 microg/g in dog's liver, 0.9 microg/g in cow's stomach and contents, 35 microg/g in elephant's stomach and contents.