Search

Many images used in media and advertising employ visual metaphors that provide enjoyment and storytelling. This study employed an image perception questionnaire to evaluate high school students’ image preferences. The results revealed that among the adjectives provided by the researcher, high school students exhibited higher preferences for describing images as creative, symbolic, cultural, artistic, contrasting, serious, exaggerated, and rational imagery. According to the independent sample t-test results, a pronounced gender difference existed in the preference of selection from the ‘Conservative–Creative’ adjective pair to describe images. Additionally, male and female students displayed higher preferences for describing fusion metaphorical images as ‘natural’ and ‘cultural’, respectively. The preferences of students of different genders for metaphorical images were considerably influenced by the conservative, creative, natural, or cultural elements of the images. According to the results of the chi-square test of independence and phi correlation coefficient test, gender exhibited a significant but low correlation with students’ preferences for juxtaposed and replacement metaphorical images. The findings of this study can provide valuable insights for art educators to gain a deeper understanding of gender differences in students’ image assessments and preferences when viewing images, helping them select appropriate visual teaching materials.

This study combined the principles of multimedia message design with an enclosing-rectangle scaffold to facilitate instruction on deriving the area of basic geometric shapes. A pretest/posttest/delayed-posttest design was used to compare the effectiveness of the enclosing-rectangle scaffold with that of conventional dissection/rearrangement methods among low-achieving seventh-grade students. These fifty-six low-achieving students were averagely assigned to one of two teaching methods. In immediate and delayed testing, an enclosing-rectangle scaffold proved significantly more effective than the conventional approach (posttest: F (1,53) = 16.148, p = <0.001, [eta][superscript 2] = 0.234; delayed posttest: F (1,53) = 13.502, p = <0.001, [eta] [superscript 2] = 0.203). These findings demonstrate the effectiveness of stepwise visualisation within a coherent context in facilitating the selection, organisation, and integration of mathematical concepts. Given the ongoing challenges that students face in comprehending the formula for calculating the area of a trapezoid, there is a need for further research in this area to identify effective instructional approaches and strategies.

Providing a safe and secure living environment for residents that is supported by a dedicated healthcare team is one of the core values of nursing homes. Nursing homes must protect residents from the risk of going missing, track quarantined residents and visitors to control the spread of infection, and maintain proactive nursing rounds. However, recruiting and retaining qualified caregivers and medical staff has long been a challenge. Therefore, using advanced technology to ensure the safety and security of residents is highly desirable. In this work, we first demonstrate the applicability of indoor tracking applications in a nursing home, such as resident and asset tracking, nursing assistant management, visitor tracking, infection control, and vital-sign monitoring. To monitor the locations of residents and staff, Bluetooth tags were used, providing real-time data for location tracking. We then conduct a series of quantitative analyses to illustrate how indoor tracking data can support the management of nursing homes, including characterizing residents’ activities in daily living and assessing the performance and workload of nursing assistants. Finally, we use qualitative research to evaluate the acceptability of an indoor positioning system in the nursing home. The results show that the implemented indoor positioning applications can improve the quality of healthcare and working efficiency, thereby providing a safer and more secure living environment for residents.

Prolonged sitting with poor posture can lead to various health problems, including upper back pain, lower back pain, and cervical pain. Maintaining proper sitting posture is crucial for individuals while working or studying. Existing pressure sensor-based systems have been proposed to recognize sitting postures, but their accuracy ranges from 80% to 90%, leaving room for improvement. In this study, we developed a sitting posture recognition system called SPRS. We identified key areas on the chair surface that capture essential characteristics of sitting postures and employed diverse machine learning technologies to recognize ten common sitting postures. To evaluate the accuracy and usability of SPRS, we conducted a ten-minute sitting session with arbitrary postures involving 20 volunteers. The experimental results demonstrated that SPRS achieved an impressive accuracy rate of up to 99.1% in recognizing sitting postures. Additionally, we performed a usability survey using two standard questionnaires, the System Usability Scale (SUS) and the Questionnaire for User Interface Satisfaction (QUIS). The analysis of survey results indicated that SPRS is user-friendly, easy to use, and responsive.