Hello, everyone. I would like to introduce a paper I read in our most recent English Literature Seminar along with my thoughts on it.

• Paper Title: Development and Evaluation of an Educational Board Game- “118 Job Bank” for Human Resource Training Courses

• Journal: European Conference on Games Based Learning

• Pages: 774-781

• Year of Publication: 2021

• Authors: Zuo Pei-Ying, Fang Ying-Sang, Kuo Chih-Chen, Lin Hsin-Ta, Hou Huei-Tse

Career planning is an essential process for students when making future vocational choices, and it is a step toward deepening their self-aptitude, interests, and vocational knowledge. In the planning process, “career exploration”—collecting information about occupations and education suitable for oneself—is a crucial element. However, career exploration for the younger generation is often accompanied by anxiety and stress, and it is believed that receiving appropriate support to alleviate these factors directly leads to learning effectiveness. Previous research has pointed out that while career exploration leads to the acquisition of career-related knowledge and improved self-awareness, the anxiety arising during the process acts as a factor that diminishes the quality of decision-making.

Game-Based Learning (GBL), which has drawn attention in recent years, is said to have the potential to contribute to learning motivation, the cultivation of problem-solving abilities, and even the reduction of learning anxiety, and its application is progressing in various fields. Against this backdrop, this paper applied GBL methods to career education and verified the hypothesis that learning outcomes could be improved by having students undergo simulated career exploration experiences through actual vocational data and role-playing.

Specifically, the objectives of this research are divided into two stages. First, we verify whether students’ career-related knowledge and decision-making abilities improve through the utilization of a career education board game called “118 Job Bank.” Second, we aim to clarify the characteristics of each mode and the consistency of learning effects by statistically verifying whether significant differences occur in flow experience, game acceptance, learning motivation, and learning anxiety across the three game modes within the board game.

The “118 Job Bank” used in this study is designed to allow learners to deepen their knowledge about careers by combining “occupational cards,” created based on actual vocational data obtained from the website of the Ministry of Labor in Taiwan, with “character cards,” constructed based on Holland’s RIASEC model. The game is composed of the following three modes, each designed with different learning effects in mind:

1. Matching Mode: “Human Resource Agency Expert” Learners act as interns at a temporary staffing agency and perform appropriate matching by comparing the presented character cards with occupational cards. It is expected that this process will cultivate the ability to understand the characteristics and skills necessary for each occupation and judge suitable professions.

2. Sequence Mode: “Salary Actuaries” In this mode, learners act as payroll clerks and estimate the starting salary for each occupation. By predicting and sequencing accurate starting salaries based on the information provided on the occupational cards, they can deepen their understanding of salary systems and market values for each profession.

3. Combination Mode: “Hunter Head Expert” Learners take on the role of headhunters selecting suitable personnel for corporate projects. By combining multiple occupational cards, the process of selecting personnel who match the skill sets and job descriptions required by the company is designed to promote strategic thinking and multifaceted analytical abilities.

A characteristic of these modes is that they allow for a simulated experience of the actual vocational market and business environment through the use of real career data, and they are expected to serve as a means for learners to cultivate practical knowledge and judgment.

In the experiment, 36 Taiwanese high school students were divided into 9 groups of 4 members each, and a 110-minute activity was conducted. A set of “118 Job Bank” was distributed to each group, and the experience of each mode during gameplay was designed to promote the acquisition of career-related knowledge and the process of decision-making. As for evaluation methods, tests were conducted before and after gameplay, and the improvement in learning achievement was analyzed using paired t-tests. Furthermore, learners’ evaluations of each game mode were assessed based on game acceptance (based on the Technology Acceptance Model: TAM), the flow scale, the learning anxiety scale, and items for learning motivation from the Motivated Strategies for Learning Questionnaire, with statistical significance verified using ANOVA.

Comparing the pre- and post-tests, a significant improvement in learning achievement (t(36)=-4.378, p<.01) was observed, clarifying that career education through games is effective for students’ knowledge acquisition and improvement of decision-making abilities. Regarding the evaluations for “game acceptance,” “flow experience,” “learning motivation,” and “learning anxiety” for each of the three game modes, high ratings were shown across all modes, confirming that career education using games achieved usability, focus on learning, and reduction of anxiety as initially intended. On the other hand, in each result, there were no significant differences in effectiveness among the three game modes.

From the above results, it can be concluded that “118 Job Bank” is an effective educational tool that allows learners to experience decision-making and strategic thinking in near-real situations through actual career data and role-playing. In particular, an important implication of this research is that it contributes not only to knowledge acquisition in career exploration but also to the reduction of learning anxiety and the improvement of learning motivation.

The results of this study show the potential for career education using educational board games to contribute to the acquisition of knowledge and improvement of decision-making abilities compared to traditional lecture-style classes. Furthermore, since each mode in the game consistently brought about high flow experiences, acceptance, and learning motivation while also confirming effects in reducing learning anxiety, the introduction of GBL in future career education is expected.

Regarding the limitations of this study, the authors state the following. First, due to time constraints, the learning content and tasks included in the game were limited, so it is necessary to secure more sufficient time for students. Additionally, this study did not analyze what kind of behavioral patterns or game strategies students adopted while playing the game, and the authors also argue for the necessity of conducting interview surveys to gain a deeper understanding of the learning process.

The following are my thoughts. In game design methods for career education, the fact that multifaceted evaluations—not only of learning effects but also of the reduction of learning anxiety and motivation toward learning—were conducted was helpful as a reference for the advantages of choosing game-based learning. On the other hand, despite designing the game with diverse game modes, the analysis was limited to paired t-tests for learning effects and ANOVA between modes, and since no significant differences in effects among modes were confirmed, I became curious about which elements influence career-related skills and other learning effects. For example, I would like to incorporate into future empirical research a comparison of how learning anxiety and motivation differ when career learning is conducted without using a game. Furthermore, as the authors suggest the necessity of analyzing behavioral patterns during gameplay, I felt there is potential for multifaceted evaluation through the use of learning analytics and the analysis of content written in post-activity worksheets, in addition to interviews. Since the authors pointed out the limitations of learning content due to the cards, I believe that career-related learning content could be reinforced through the use of ICT, such as visual support utilizing AR or referring to databases using QR codes, making this a field where further research expansion can be expected.

By: Kohei Ozaki