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This article paper explores the evaluation of artificial intelligence (AI) in English as a Foreign Language (EFL) writing courses and the importance of calibration in writing evaluations. The role of calibration has received little attention in language contexts, while the role of artificial intelligence has gained increased attention in the last couple of years. This investigation, conducted from August 2022 to March 2023, involved eight TESOL students enrolled in an English as a Foreign Language (EFL) major at a Costa Rican public university, ten TESOL university professors, and one AI piece of software. It used a quantitative, quasi-experimental design, and a language elicitation data collection process. Data was collected by means of a rubric-based writing assessment. Quantitative data were analyzed using descriptive statistics. Data analyses indicate that: 1) human-created paragraphs (X̄ = 7,56) and AI writing (X̄ = 7,61) yield similar results when evaluated; 2) some criteria may favor human creativity or computer, rule-oriented writing; and 3) professors’ ratings reveal inconsistencies when grading human writing in particular. These findings demonstrate that AI matches, at least to a basic level, human writing skills. Furthermore, data show that students may be falling behind in aspects such as grammar, vocabulary, and mechanics. Finally, the analysis indicates that professors’ grading lacks consistency, and a calibration model should be incorporated as part of regular training workshops.

Technical Vocational Education and Training (TVET) in Costa Rica is considered as an important alternative for the insertion of the young population into the labor market. However, despite the increasing importance of TVET there is a lack of institutionalized research activities, so that research efforts on TVET mainly remain in the background. The aim of this paper is to present and examine the level of institutionalization of TVET research in Costa Rica and the associated needs, challenges, and demands. Therefore, qualitative research, with an exploratory scope, was conducted between December 2022 and June 2023, for which a literature review on TVET research and semi-structured interviews with sixteen experts were carried out. The results revealed, that from 2020 to date, there has been an increase in the number of research activities in TVET and in the number of publications in Costa Rican journals. Nevertheless, TVET institutions in Costa Rica show low capacities in terms of personnel and financial resources to conduct TVET research. The main conclusion is that the level of institutionalization of TVET Research in Costa Rica is in its infancy, but has potential for growth, for which it is necessary to establish public TVET policies that include TVET research.

Technical Vocational Education and Training (TVET) in Costa Rica is considered as an important alternative for the insertion of the young population into the labor market. However, despite the increasing importance of TVET there is a lack of institutionalized research activities, so that research efforts on TVET mainly remain in the background. The aim of this paper is to present and examine the level of institutionalization of TVET research in Costa Rica and the associated needs, challenges, and demands. Therefore, qualitative research, with an exploratory scope, was conducted between December 2022 and June 2023, for which a literature review on TVET research and semi-structured interviews with sixteen experts were carried out. The results revealed, that from 2020 to date, there has been an increase in the number of research activities in TVET and in the number of publications in Costa Rican journals. Nevertheless, TVET institutions in Costa Rica show low capacities in terms of personnel and financial resources to conduct TVET research. The main conclusion is that the level of institutionalization of TVET Research in Costa Rica is in its infancy, but has potential for growth, for which it is necessary to establish public TVET policies that include TVET research.

This article paper explores the evaluation of artificial intelligence (AI) in English as a Foreign Language (EFL) writing courses and the importance of calibration in writing evaluations. The role of calibration has received little attention in language contexts, while the role of artificial intelligence has gained increased attention in the last couple of years. This investigation, conducted from August 2022 to March 2023, involved eight TESOL students enrolled in an English as a Foreign Language (EFL) major at a Costa Rican public university, ten TESOL university professors, and one AI piece of software. It used a quantitative, quasi-experimental design, and a language elicitation data collection process. Data was collected by means of a rubric-based writing assessment. Quantitative data were analyzed using descriptive statistics. Data analyses indicate that: 1) human-created paragraphs (X̄ = 7,56) and AI writing (X̄ = 7,61) yield similar results when evaluated; 2) some criteria may favor human creativity or computer, rule-oriented writing; and 3) professors’ ratings reveal inconsistencies when grading human writing in particular. These findings demonstrate that AI matches, at least to a basic level, human writing skills. Furthermore, data show that students may be falling behind in aspects such as grammar, vocabulary, and mechanics. Finally, the analysis indicates that professors’ grading lacks consistency, and a calibration model should be incorporated as part of regular training workshops.