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Experimental And Quasi Experimental Designs For Research

The focus of higher education institutions is the preparation of future professionals. To achieve this aim, innovative teaching methods are often deployed, including games and simulations, which form the subject of this paper. As the field of digital games and simulations is ever maturing, this paper attempts to systematically review the literature relevant to games and simulation pedagogy in higher education. Two researchers collaborate to apply a qualitative method, coding and synthesizing the results using multiple criteria. The main objective is to study the impact of games and simulations with regard to achieving specific learning objectives. On balance, results indicate that games and/or simulations have a positive impact on learning goals. The researchers identify three learning outcomes when integrating games into the learning process: cognitive, behavioural, and affective. As a final step, the authors consolidate evidence for the benefit of academics and practitioners in higher education interested in the efficient use of games and simulations for pedagogical purposes. Such evidence also provides potential options and pathways for future research.

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The effect of games and simulations on higher education: a systematic literature review

This article is a survey of program visualization systems intended for teaching beginners about the runtime behavior of computer programs. Our focus is on generic systems that are capable of illustrating many kinds of programs and behaviors. We inclusively describe such systems from the last three decades and review findings from their empirical evaluations. A comparable review on the topic does not previously exist; ours is intended to serve as a reference for the creators, evaluators, and users of educational program visualization systems. Moreover, we revisit the issue of learner engagement which has been identified as a potentially key factor in the success of educational software visualization and summarize what little is known about engagement in the context of the generic program visualization systems for beginners that we have reviewed; a proposed refinement of the frameworks previously used by computing education researchers to rank types of learner engagement is a side product of this effort. Overall, our review illustrates that program visualization systems for beginners are often short-lived research prototypes that support the user-controlled viewing of program animations; a recent trend is to support more engaging modes of user interaction. The results of evaluations largely support the use of program visualization in introductory programming education, but research to date is insufficient for drawing more nuanced conclusions with respect to learner engagement. On the basis of our review, we identify interesting questions to answer for future research in relation to themes such as engagement, the authenticity of learning tasks, cognitive load, and the integration of program visualization into introductory programming pedagogy.

A Review of Generic Program Visualization Systems for Introductory Programming Education

Transformation-based learning has been successfully employed to solve many natural language processing problems. It achieves state-of-the-art performance on many natural language processing tasks and does not overtrain easily. However, it does have a serious drawback: the training time is often intorelably long, especially on the large corpora which are often used in NLP. In this paper, we present a novel and realistic method for speeding up the training time of a transformation-based learner without sacrificing performance. The paper compares and contrasts the training time needed and performance achieved by our modified learner with two other systems: a standard transformation-based learner, and the ICA system \cite{hepple00:tbl}. The results of these experiments show that our system is able to achieve a significant improvement in training time while still achieving the same performance as a standard transformation-based learner. This is a valuable contribution to systems and algorithms which utilize transformation-based learning at any part of the execution.

Transformation-Based Learning in the Fast Lane

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Text generation

Software process modeling (SPM) is an important area of software engineering because it provides a basis for managing, automating, and supporting software process improvement (SPI). Teaching SPM is a challenging task, mainly because it lays great emphasis on theory and offers few practical exercises. Furthermore, as yet few teaching approaches have aimed at teaching SPM by introducing innovative features, such as games. The use of games has mainly been focused on other areas of software engineering, for example software project management. In an attempt to fill this gap, this paper describes a formal experiment carried out to assess the learning effectiveness of a serious game (DesigMPS), designed to support the teaching of SPM, and to compare game-based learning with a project-based learning method. In the DesigMPS game, the student models a software process from an SPI perspective, based on the Brazilian SPI model (MPS.BR). The results indicate that playing the game can have a positive learning effect and results in a greater degree of learning effectiveness than does the project-based learning instructional method.

Experimental Evaluation of a Serious Game for Teaching Software Process Modeling

In this article we discuss the use of concept maps (CMs) in learning assessment. As an alternative to the comparison of the learner’s CM with the teacher’s CM, in order to certify what is right or wrong or to attribute a grade, we present a new approach to assess CMs: we consider learning assessment as an adaptive and evolutionary problem and we show how to use ontologies and machine learning, through genetic algorithms (GAs), to assess CMs. The ontologies we use store knowledge, in the form of concepts and propositions, and functions to measure the semantic distance between CMs. The GA, using the ontology, generates the search space (collections of CMs) used to show learners the alternatives to their possible faults when learning concepts and propositions. The complete assessment of a CM includes the analysis of its hierarchical structure, the recognition of learning types, and the analysis of semantic similarity with the CMs of the search space. We also show the actions executed by the GA to construct the CMs of the search space and the concepts present in the ontology and ignored by the learner.

A new approach to meaningful learning assessment using concept maps: ontologies and genetic algorithms

Este artigo demonstra a incorporacao no JavaTool, ja em uso e integrado a plataforma Moodle, recursos que possibilitem o exercicio do feedback entre estudantes, como forma de estimular o desenvolvimento de habilidades de avaliacao. Pesquisas tem sido realizadas com o intuito demostrar a competencias de autoavaliacao concentrando-se esforcos na proposta do subsistema de feedback colaborativo. Este artigo traz uma contribuicao importante na discussao da avaliacao automatica nao apenas como um instrumento de avaliacao, com a finalidade de reduzir a sobrecarga do professor, mas como um componente que apoia os processos de autorregulacao da aprendizagem.

Aprendizagem de iniciantes em algoritmos e programação: foco nas competências de autoavaliação

Computerized analysis of a concept map (CM) syntactic and semantic characteristics can become a complex task, whose results can be doubtful if the map contains either graphical or textual ambiguities. In the specific case of using CMs in education, the use of the results of automatic structural analysis of a map in learning assessment implies the existence of entirely computable maps, capable of coping with the inherently ambiguous nature of the language used in their construction, which results in imprecise concepts and linking phrases. This imprecision hinders initiatives toward computer processing of CMs. In this paper, we present a strategy to minimize the imprecision of linking phrases, by analyzing the nature of inclusivity in hierarchies of concepts in CMs. We present a formal extensible notation capable of distinguishing among the subtleties of these hierarchies. Based on this formalization, it is possible not only to determine precisely the dimension of inclusivity specified in a proposition, but also to define methods capable of determining the semantic distance between propositions in CMs.

http://cmc.ihmc.us/papers/cmc2004-242.pdf

Linking Phrases in Concept Maps: A Study on the Nature of Inclusivity

This paper presents research of an application of a latent semantic analysis (LSA) model for the automatic evaluation of short answers (25 to 70 words) to open-ended questions. In order to reach a viable application of this LSA model, the research goals were as follows: (1) to develop robustness, (2) to increase accuracy, and (3) to widen portability. The methods consisted of the following tasks: firstly, the implementation of word bigrams; secondly, the implementation of combined models of unigrams and bigrams using multiple linear regression; and, finally, the addition of an adjustment step after the score attribution taking into consideration the average of the words of the answers. The corpus was composed by 359 answers produced according to two questions from a Brazilian public university’s entrance examination, which were previously scored by human evaluators. The results demonstrate that the experiments produced accuracy about 84.94 %, while the accuracy of the two human evaluators was about 84.93 %. In conclusion, it can be seen that the automatic evaluation technology shows that it is reaching a high level of efficiency.

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Eloi Luiz Favero

Papers

Experimental Evaluation of a Serious Game for Teaching Software Process Modeling

A new approach to meaningful learning assessment using concept maps: ontologies and genetic algorithms

Aprendizagem de iniciantes em algoritmos e programação: foco nas competências de autoavaliação

Linking Phrases in Concept Maps: A Study on the Nature of Inclusivity

Practical use of a latent semantic analysis (LSA) model for automatic evaluation of written answers