The effects of first programming language on college students’ computing attitude and achievement: a comparison of graphical and textual languages

Background and Context: The relationship between novices’ first programming language and their future achievement has drawn increasing interest owing to recent efforts to expand K–12 computing education. This article contributes to this topic by analyzing data from a retrospective study of more than 10,000 undergraduates enrolled in introductory computer science courses at 118 U.S. institutions of higher education.

Objective: We explored the relationship between students’ first programming languages and both their final grades in an introductory computer science course and their attitudes about programming.

Method: Multiple matching techniques compared those whose first language was graphical (e.g., Scratch), textual (e.g., Java), or absent prior to college.

Findings: Having any prior programming experience had positive effects on both attitudes about programming and grades in introductory computer science courses. Importantly, students whose first language was graphical had higher grades than did students whose first language was textual, when the languages were introduced in or before early adolescent years.

Implications: Learning any computer language is better than learning none. If programming is to be taught to students before early adolescence, it is advised to start with a graphical language. Future work should investigate the transition between different types of programming languages.     

Components of fostering self-regulated learning among students. A meta-analysis on intervention studies at primary and secondary school level

Due to new standards in fostering life-long learning at school, research has increasingly dealt with the promotion of self-regulated learning, resulting in a large number of intervention studies conducted at primary and secondary school. The current study aimed at investigating the impact of various training characteristics on the training outcomes, regarding academic performance, strategy use and motivation of students. Two meta-analyses were conducted separately, one for primary and one for secondary school level to allow for comparisons between both school levels. The meta-analyses included 49 studies conducted with primary school students and 35 studies conducted with secondary school students; analyzing 357 effect sizes altogether. The potential effects of training characteristics were investigated by means of meta-analytic multiple regression analyses. The average effect size was 0.69. For both school levels, effect sizes were higher when the training was conducted by researchers instead of regular teachers. Moreover, interventions attained higher effects when conducted in the scope of mathematics than in reading/writing or other subjects. Self-regulated learning can be fostered effectively at both primary and secondary school level. However, the theoretical background on which the training programme is based, as well as the type of instructed strategy led to differential effects at both school levels.

Das MeDoc-System – ein elektronischer Publikations- und Nachweisdienst für die Informatik

Zusammenfassung.   Ziele des MeDoc-Projektes waren die Konzeption, prototypische Entwicklung und Erprobung volltextbasierter Informations- und Publikationsdienste für die Informatik, um den Informationsaustausch und die Literaturversorgung in der Wissenschaft effektiver gestalten zu k?nnen. Dazu wurde im Rahmen des Projektes ein internet-basiertes System entwickelt, in dem Informatik & Fachinformation im Volltext gespeichert, recherchiert, abgerufen und gelesen werden kann und das die Suche nach Informatik-Literatur in heterogenen, verteilten Informationsquellen im Internet unterstützt. Das Informationsangebot ist dabei teilweise kostenpflichtig. In diesem Artikel werden Ziele, Funktionalit?t und Architektur des MeDoc-Systems beschrieben. Eingegangen am 19. Januar 1998 / Angenommen am 27. April 1998     

Order Matters: Sequencing Scale-Realistic Versus Simplified Models to Improve Science Learning

Teachers choosing between different models to facilitate students’ understanding of an abstract system must decide whether to adopt a model that is simplified and striking or one that is realistic and complex. Only recently have instructional technologies enabled teachers and learners to change presentations swiftly and to provide for learning based on multiple models, thus giving rise to questions about the order of presentation. Using disjoint individual growth modeling to examine the learning of astronomical concepts using a simulation of the solar system on tablets for 152 high school students (age 15), the authors detect both a model effect and an order effect in the use of the Orrery, a simplified model that exaggerates the scale relationships, and the True-to-scale, a proportional model that more accurately represents the realistic scale relationships. Specifically, earlier exposure to the simplified model resulted in diminution of the conceptual gain from the subsequent realistic model, but the realistic model did not impede learning from the following simplified model.     

Parallel assessment of nutrition and activity in athletes: validation against doubly labelled water, 24-h urea excretion, and indirect calorimetry

The assessment of nutrition and activity in athletes requires accurate and precise methods. The aim of this study was to validate a protocol for parallel assessment of diet and exercise against doubly labelled water, 24-h urea excretion, and respiratory gas exchange. The participants were 14 male triathletes under normal training conditions. Energy intake and doubly labelled water were weakly associated with each other (r = 0.69, standard error of estimate [SEE] = 304 kcal x day(-1)). Protein intake was strongly correlated with 24-h urea (r = 0.89) but showed considerable individual variation (SEE = 0.34 g kg(-1) x day(-1)). Total energy expenditure based on recorded activities was highly correlated with doubly labelled water (r = 0.95, SEE = 195 kcal x day(-1)) but was proportionally biased. During running and cycling, estimated exercise energy expenditure was highly correlated with gas exchange (running: r = 0.89, SEE = 1.6 kcal x min(-1); cycling: r = 0.95, SEE = 1.4 kcal x min(-1)). High exercise energy expenditure was slightly underestimated during running. For nutrition data, variations appear too large for precise measurements in individual athletes, which is a common problem of dietary assessment methods. Despite the high correlations of total energy expenditure and exercise energy expenditure with reference methods, a correction for systematic errors is necessary for the valid estimation of energetic requirements in individual athletes.