Corrosion is the leading reason for reinforced concrete structures reduced service life. Structures such as ports and harbors and bridges and other offshore and near shore are prone to chloride-induced corrosion. This research evaluates the use of self-compacting concrete (SCC) as an alternative concrete for such structures. In theory, SCC reduced water content, and high cement and powder content will help protect the reinforcement from chloride intrusion because of its lower porosity and the alkalinity that the cement provided. Sixteen different mixtures of SCCs were mixed and tested for rheology, compressive strength, rapid chloride ion penetration test (RCPT), and impressed current (IC). Water content is the significant factor that affects both RCPT and IC. The segregation of SCC when too much water-cement ratio is combined with a high amount of superplasticizer resulted in a high level of corrosion in the reinforcement. The formation of cracks accelerates the corrosion due to the increased flow of current in the IC set-up. The impressed current technique is the suggested method for determining the corrosion resistance of concrete since it simulates the similar effect of corrosion to concrete which is cracking. It also stimulates the effect of rust on the flow of current. A rapid chloride penetration test is a good indicator of the durability of concrete but may be insignificant for predicting the corrosion level of reinforcement for SCC. Segregation negatively affects the total charge passed in the impressed current and the corrosion level of the rebar.

Serious game is one of the pedagogical media capable of transferring knowledge to its players. This game genre requires a support system that adaptively selects the appropriate scenario for players to increase their interest and comfort. Therefore, this study proposed an adaptive scenario selection (ASS) system using a finite state machine based on an artificial neural network (ANN). The game scenario is selected by ASS based on five player preferences, including work, hobbies/interests, origin, group members, and repetition. Furthermore, the multi-layer perceptron (MLP) architecture was used in the scenario selection process for the proposed ANN method. The experimental stage was carried out using the theme of travel in several tourism destinations in Batu City, East Java, Indonesia. The experimental results show that ASS succeeded in generating adaptive game scenario choices for players based on their preference data with an accuracy of 67.25%.

When it comes to asynchronous online learning, the literature recommends multimedia content like videos of lectures and demonstrations. However, the lack of emotional connection and the absence of teacher support in these video materials can be detrimental to student success. We proposed incorporating talking heads and annotations to alleviate these weaknesses. In this study, we investigated the cognitive and affective effects of integrating these solutions in asynchronous video lectures. Guided by the theoretical lens of Cognitive Theory of Multimedia Learning and Cognitive-Affective Theory of Learning with Media, we produced a total of 72 videos (average = four videos per subtopic) with a mean duration of 258 seconds (range = 193 to 318 seconds). To comparatively assess our video treatments (i.e., regular videos, videos with face, videos with annotation, or videos with face and annotation), we conducted an educational-based cluster randomized controlled trial within a 14-week academic period with four cohorts of students enrolled in an introductory web design and development course. We recorded a total of 42,425 total page views (212.13 page views per student) for all web browsing activities within the online learning platform. Moreover, 39.92% (16,935 views) of these page views were attributed to the video pages accumulating a total of 47,665 minutes of watch time. Our findings suggest that combining talking heads and annotations in asynchronous video lectures yielded the highest learning performance, longest watch time, and highest satisfaction, engagement, and attitude scores. These discoveries have significant implications for designing video lectures for online education to support students’ activities and engagement. Therefore, we concluded that academic institutions, curriculum developers, instructional designers, and educators should consider these findings before relocating face-to-face courses to online learning systems to maximize the benefits of video-based learning.

The impact of digital games on chemistry education has received less attention compared to other scientific fields. This research gap resulted in a limited understanding of how to effectively design mobile chemistry games (MCG) distinct from non-science mobile learning games (MLG). This study aims to explore students' attitudes toward MCG and gather their opinions on the game components using a mixed-methods research design. A total of 698 students from urban universities, categorized into technology, chemistry, and education cohorts based on their academic majors, participated to provide diverse perspectives. The results revealed significant disparities in gameplay experience, particularly in competence and relatedness, between MLG and MCG. Students' educational background significantly influenced their confidence and leisure levels. Concerningly, students exhibited a negative attitude towards MCG. The study provides game developers with a guideline for developing MCG and offers chemistry teachers a framework for selecting appropriate MLG in the context of chemistry education.

The education sector is constantly progressing its competency paradigm by establishing a nexus between practical, theoretical, and technical dimensions of teaching and learning. In the modern age of education, hackathons are becoming increasingly prominent in providing an optimal academic environment that connects classroom learnings to real‐life scenarios. This study explored the motivational orientation behind student participation in hackathons through the framework provided by self‐determination theory. Specifically, it investigated the role of intrinsic and extrinsic motivations in encouraging initial and continuous hackathon participation. The partial least squares‐structural equation modeling method was used to analyze data collected from 437 students in 12 countries. According to the findings, although intrinsic motivation influences participation intention, extrinsic motivation drives continuance participation. When intrinsic and extrinsic motivational constructs were analyzed individually, it was found that continuance participation demands both motivational orientations. Comparisons of demographic characteristics indicate that older students with more extensive educational experience may have higher intentions to participate and continue participating in these events. This study offers insights into how the education sector can increase hackathon participation by tapping on students’ motivational orientation. From a methodological point of view, it is apparent to recommend the promotion of hackathons as a core extracurricular activity at a school level, and more indispensably, as pedagogy at a classroom level. In a world where students are encouraged to fail early, fast, and often, participating in hackathons is a tactical preparation for eventual success.

Due to the advent of the COVID-19 pandemic, the Philippine government encouraged enterprises and businesses to utilize flexible work arrangements such as work-from-home (WFH) or telecommuting setup. Nowadays, the key components necessary for a telecommuting include a WiFi-enabled IT equipment, secured work environment, and reliable internet connection, while research shows that type of work and computer literacy are also key factors for telework implementation. Multiple studies in relation to telework have already been conducted but some studies were deemed inconclusive and need further analysis. Therefore, in this study, a Mamdani fuzzy-based model was developed for telework capability assessment for Philippine government employees based on four significant factors namely: internet speed, IT equipment availability, computer literacy, and type of work, which are expressed in linguistic representations. The proposed fuzzy system can provide a feedback telework capability score based on the four input parameters which may also be characterized with the potential telecommuting cost requirement.

Interest in FRP composite bars as reinforcement to concrete has increased over the years as it showed solutions to the drawbacks of steel such as its corrosion issues and vulnerability when employed in adverse environmental conditions. However, it is still not widely incorporated as a replacement to conventional steel primarily due to the complexity of its bond strength mechanism. This, therefore, imposes the need to establish a comprehensive relationship for the bond property of the FRP reinforced concrete. This paper developed a novel Artificial Neural Network (ANN) bond strength prediction model for FRP reinforced concrete using 184 hinged beam database from various existing experiments. From series of simulations performed, the model N 7-10-1 with ten nodes in the hidden layer appeared to be the best fit with the experimental results yielded the most favorable performance among other existing models. From the parametric analysis conducted, the compressive strength of the FRP reinforced concrete has proved to be the most dominant parameter in evaluating its bond behavior as determined by relative importance of 17.82%. Overall, the proposed ANN model has demonstrated the best prediction for FRP bond strength in comparison to previous studies and code equations.

Social relationships are a fundamental aspect of human existence. Unsurprisingly, policymakers are incessantly devising strategies that accentuate the benefits of social relationships and diminish the risks of social isolation. The natural manifestation of player-to-player interaction in a video game context poses a unique opportunity to study the effects of co-playing on social relationship formation. However, most studies recruited players with existing relationships (e.g., family and friendship), utilized random commercial video games, or experimented in an online environment. These research gaps warrant further investigation on the utility of video games for promoting social relationships among unacquainted players while in the same physical space. Thus, this study presents the development and evaluation of a couch cooperative video game grounded on sequential team-building mechanics. The findings of this study offer empirical evidence that would have significant practical implications for any organization seeking to increase teamwork and cooperation among its members.

Location-based marketing (LBM) is becoming an integral element of the media mix for making highly personalised offers to the targeted audience at the most opportune time and place. Yet, the literature calls for more usability studies due to the lack of user-centred research. To fill this gap, this study explores the development of PushMapp - a geomarketing tool for launching LBM campaigns - through a user-centred, parallel-iterative approach. Usability analysis shows that this type of application is affected by issues related to security, privacy, advertisement relevancy, and notification overload. Meanwhile, only performance expectancy, effort expectancy, and hedonic motivation appeared to be the significant factors in an LBM mobile application. Experiences from this study provided valuable insights for marketers and business owners who plan to capitalise on LBM strategies by underscoring the importance of integrating users' input, ensuring usability compliance, and conforming to factors of mobile application utilisation.

Urban systems have a central role in the transition toward circular economy. Systematic analysis of drivers is needed because of the complex interplay of social, economic, and political factors. Such analysis requires a good understanding of direct and indirect influences on urban circularity. Because of the presence of indirect influences, visualizing the causal networks is necessary for systematic analysis. Existing methods for formulating causal network maps (CNMs) rely on subjective approaches which inhibit robust assessment. The generation of robust CNMs can provide more accurate representation of direct and indirect influences. Therefore, this study generates a robust CNM for drivers of urban circular economy through a hybrid decision-making and trial laboratory-fuzzy cognitive map (DEMATEL-FCM) framework. DEMATEL is used for building the initial structure of the network map. The network is then trained using FCM with data obtained from the Sustainable Cities Index. A 70:30 training–testing ratio is used to partition the training and testing datasets. The trained CNM has 92.75% accuracy during training and 96.77% accuracy during testing. The trained CNM provides an empirical depiction of driver interrelationships in urban circular economies. It indicates the importance of ‘affordability’ and ‘economic development’ in the network structure. The network yields significant insights for the development of city-level plans and policies to stimulate a transition to a more circular economy. Data-driven visualization of interactions among drivers give stakeholders insights on the most effective measures to implement.