Block-based programming languages (BBLs) have been proposed as a way to prepare students for learning to program in more sophisticated, text-based languages, such as Java. Hybrid BBLs add the ability to view and edit the block commands in auto-generated, text-based code. We compared the use of a non-hybrid BBL (Scratch), a hybrid BBL (Pencil Code), and no BBL across three sections of an introductory CS course that taught Java programming, to determine whether either type of BBL offered cognitive or affective advantages for learning Java. Students in the BBL groups were surveyed about their perceptions of each BBL in terms of ease of use and helpfulness in learning Java, and all three groups were compared on their performance in Java programming. The results showed that, in this introductory CS course, neither type of BBL offered an advantage in preparing students for learning Java. These results held regardless of the students’ level of Java knowledge prior to the course.

This study examined the relationship between stress and social media usage, whether stress was an indicator of social media use, and tested moderators of the relationship between stress and social media use. Participants ( n = 201) were randomly assigned to a stress-inducing recall activity or a control task via an online survey. Next, they completed measures of stress, social media usage, social support, and habitual behavior. We found that seeking social support contributed to an increased usage of social media. In addition, increased usage of social media was related to greater frequency and strength of evoking habitual behavior.

Electronic word of mouth (eWoM) is one of the most valuable resources available to consumers in the search for products and services. This paper presents a novel recommendation system in which eWoM citations compiled using search engines are filtered according to the preferences and requirements of users. The proposed mechanism uses descriptive term creation to formalize the language used in searches, which is then classified according to the Rational Decision Making model to facilitate the analysis of eWoM. The proposed system was evaluated by applying it to the search for dental services in Chungli, Taiwan. Experiment results show that the proposed system reduces the time and effort required to sift through search results. Participants reported that the proposed system excels in quality and effectiveness and had a positive effect on their satisfaction and behavioral intentions. From a managerial perspective, the proposed system provides a valuable tool with which to improve service quality by identifying areas in which previous users have provided negative commentary via eWoM.

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