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The purpose of this paper was to develop a predictor model for an online nutrition course on sugar reduction. The proposed model is based on health knowledge, healthy behavior, social support, self-efficacy, attitude and the health belief model in relation to people’s behavior within a Facebook group. Subsequently, the model can be used to design a robust online training course for human resources, thereby reducing the training costs which managers have experienced as being expensive.

A single pre-post experimental group design was used. Pre and post data were collected from 100 Facebook users using an online questionnaire, within a three-week intervention.

The results show a significant difference between pre- and post-test scores of health knowledge and healthy behavior, indicating an effective intervention. In addition, perceived barriers, attitude, self-efficacy and emotional support were significant predictors of the healthy behavior model, predicting 70 percent of healthy behavior. However, knowledge had no significant relationship with any of the three dependent variables (self-efficacy, attitude and healthy behavior) proposed.

This model has proved to be an effective intervention which can be used in online training of human resources, because the content of the training is known from the predictor model, thereby greatly reducing the training cost, since everything is done online. Moreover, the provided model and predictors show that the content to be delivered in the training program is not knowledge but perceived barriers, attitude, self-efficacy and emotional support.

This study is one of the first to propose an integrative model that suggests attitude and self-efficacy as key predictors of healthy behavior whereas knowledge is not.

Advancements in technology require that everyone is skilled with computational thinking (CT), problem-solving and computer programming skills. This study aims to examine the development of CT in problem-solving skills (PSS) and programming learning attitude by integrating LEGO robotics kits in a project-based learning course.

This study examines the development of CT in PSS and programming learning attitude by integrating LEGO robotics kits in a project-based learning course. This study consists of a single group pre-post-test research design with 32 freshmen university students. Quantitative and qualitative data were collected by pre-post-tests and recording of classroom discussions, respectively.

Therefore, this finding implies that robotics can be used to develop CT in university students; however, there is a need for designing curricula with advanced robotic kits as artificial intelligence (AI) has become more prevalent. Hence, programming knowledge learned will help students to understand the application of robots in AI.

The study creates educators' awareness that CT skills might be developed in freshmen university students through robotics. However, many still consider them toys rather than learning aids.