scholarly journals Using Web-Based Repository of Testing Tutorials (WReSTT) with a Cyber Learning Environment to Improve Testing Knowledge of Computer Science Students

2018 ◽  
Author(s):  
Hakam Alomari ◽  
James Kiper ◽  
Gursimran Walia ◽  
Katharine Zaback
Keyword(s):  
Learning Environment ◽  
Computer Science ◽  
Science Students ◽  
Web Based ◽  
Cyber Learning

A web-based language learning environment: general architecture

ReCALL ◽  
1999 ◽  
Vol 11 (S1) ◽  
pp. 31-39
Author(s):  
Pierre-Yves Foucou ◽  
Natalie Kübler
Keyword(s):  
Learning Environment ◽  
Language Learning ◽  
Computer Science ◽  
Subject Area ◽  
Point Of View ◽  
Learning Activities ◽  
Web Based ◽  
Wide Range ◽  
General Architecture ◽  
The Web

In this paper, we present the Web-based CALL environment (or WALL) which is currently being experimented with at the University of Paris 13 in the Computer Science Department of the Institut Universitaire de Technologie. Our environment is being developed to teach computer science (CS) English to CS French-speaking students, and will be extended to other languages for specific purposes such as, for example, English or French for banking, law, economics or medicine, where on-line resources are available.English, and more precisely CS English is, for our students, a necessary tool, and not an object of study. The learning activities must therefore stimulate the students' interest and reflection about language phenomena. Our pedagogical objective, relying on research acquisition (Wokusch 1997) consists in linking various texts together with other documents, such as different types of dictionaries or other types of texts, so that knowledge can be acquired using various appropriate contexts.Language teachers are not supposed to be experts in fields such as computer sciences or economics. We aim at helping them to make use of the authentic documents that are related to the subject area in which they teach English. As shown in Foucou and Kübler (1998) the wide range of resources available on the Web can be processed to obtain corpora, i.e. teaching material. Our Web-based environment therefore provides teachers with a series of tools which enable them to access information about the selected specialist subject, select appropriate specialised texts, produce various types of learning activities and evaluate students' progress.Commonly used textbooks Tor specialised English offer a wide range of learning activities, but they are based on documents that very quickly become obsolete, and that are sometimes widely modified. Moreover, they are not adaptable to the various levels of language of the students. From the students' point of view, working on obsolete texts that are either too easy or too difficult can quickly become demotivating, not to say boring.In the next section, we present the general architecture of the teaching/learning environment; the method of accessing and using it, for teachers as well as for students, is then described. The following section deals with the actual production of exercises and their limits. We conclude and present some possible research directions.

Computer Science Meets Education: Natural Language Processing for Automatic Grading of Open-Ended Questions in eBooks

2020 ◽  
Vol 58 (7) ◽  
pp. 1227-1255
Author(s):  
Glenn Gordon Smith ◽  
Robert Haworth ◽  
Slavko Žitnik
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Arts ◽  
Computer Science ◽  
Language Processing ◽  
Real World ◽  
Fourth Grade ◽  
Science Students ◽  
Web Based ◽  
Science Professor

We investigated how Natural Language Processing (NLP) algorithms could automatically grade answers to open-ended inference questions in web-based eBooks. This is a component of research on making reading more motivating to children and to increasing their comprehension. We obtained and graded a set of answers to open-ended questions embedded in a fiction novel written in English. Computer science students used a subset of the graded answers to develop algorithms designed to grade new answers to the questions. The algorithms utilized the story text, existing graded answers for a given question and publicly accessible databases in grading new responses. A computer science professor used another subset of the graded answers to evaluate the students’ NLP algorithms and to select the best algorithm. The results showed that the best algorithm correctly graded approximately 85% of the real-world answers as correct, partly correct, or wrong. The best NLP algorithm was trained with questions and graded answers from a series of new text narratives in another language, Slovenian. The resulting NLP algorithm model was successfully used in fourth-grade language arts classes for providing feedback to student answers on open-ended questions in eBooks.

Integrated Software Testing Learning Environment for Training Senior-Level Computer Science Students

2009 ◽  
pp. 2029-2045
Author(s):  
Daniel Bolanos ◽  
Almudena Sierra
Keyword(s):  
Learning Environment ◽  
Computer Science ◽  
Software Testing ◽  
Statistical Significance ◽  
Science Students ◽  
Testing Tools ◽  
Testing Techniques ◽  
Students Attitudes ◽  
Integrated Software

Due to the increasingly important role of software testing in software quality assurance, during the last several years, the utilization of automated testing tools, and particularly those belonging to the xUnit family, has proven to be invaluable. However, as the number of resources available continues increasing, the complexity derived from the selection and integration of the most relevant software testing principles, techniques and tools into an adequate learning environment for training computer science students in software testing, increases too. In this chapter we introduce a experience of teaching Software Testing for a senior-level course. In the elaboration of the course a wide variety of testing techniques, methodologies and tools have been selected and seamlessly integrated. An evaluation of students performance during the three academic years that the course has been held show that students’ attitudes changed with a high or at least a positive statistical significance.

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