Enhancing Student Engagement in Blended Learning Through Personalization Strategies on EdTech Platforms

Determining road handling priority is considered as a complicated multicriteria decision making problem. In so doing, the Analytic Hierarchy Process (AHP) has been widely used to weight the importance. Fuzziness and vagueness however, are typical in many decision-making problems, so that fuzzy sets could be integrated with the pairwise comparison as an extension of the AHP. This study uses Fuzzy Analytic Hierarchy Process (FAHP) and TOPSIS method in determining regencial road handling priority for road links under severe circumstances in Badung regency in Bali province. Data are taken from a previous study, which had also been conducted for Badung regencial road handling priority using the AHP and SK.NO.77/KPTS/Db/1990 method. The weights of main and sub criteria are determined using FAHP and subsequently the ranking of road links is determined using TOPSIS method. The AHP method gave somewhat different result to 'SK.NO.77/KPTS/Db/1990' method. On the other hand, FAHP and TOPSIS method produce the same result to 'SK.NO.77/KPTS/Db/1990' method. This is probably best explained by the fact that they similarly considered traffic volumes as the most significant factor. FAHP and TOPSIS method however, are preferred to the AHP and SK.NO.77/KPTS/Db/1990 method in determining regencial road handling priority in Badung regency.Abstrak. Prioritas penanganan jalan merupakan salah satu tugas berat dan penting yang dihadapi oleh pengambil keputusan pada pemerintah daerah. Pada kenyataannya, penentuan penanganan jalan dapat dilihat sebagai permasalahan pengambilan keputusan yang melibatkan banyak kriteria yang bersifat kompleks. Metode proses hirarki analitik (AHP) telah banyak digunakan untuk menentukan bobot kriteria di dalam penentuan prioritas penanganan jalan. Akan tetapi karena keragu-raguan merupakan hal yang lazim terjadi di dalam pengambilan keputusan, maka teknik fuzzy dapat dikombinasikan ke dalam metode AHP. Pada studi ini penentuan prioritas penanganan jalan kabupaten untuk kondisi rusak berat di Kabupaten Badung, Bali dilakukan dengan metode Fuzzy AHP (FAHP) dan TOPSIS. Data penelitian digunakan dari studi sebelumnya di Kabupaten Badung yang menggunakan metode AHP dan SK.NO.77/KPTS/Db/1990. Metode FAHP digunakan untuk pembobotan kriteria sedangkan metode TOPSIS digunakan untuk penentuan urutan ruas jalan yang akan mendapat penanganan. Metode AHP memberikan hasil yang sedikit berbeda dengan metode SK.NO.77/KPTS/Db/1990. Sementara itu FAHP dan metode TOPSIS memberikan hasil yang sama dengan metode SK.NO.77/KPTS/Db/1990. Hal ini kemungkinan karena kedua metode tersebut menggunakan volume lalu lintas sebagai faktor yang paling berpengaruh pada penelitian ini. FAHP dan metode TOPSIS lebih disarankan untuk digunakan di dalam penentuan prioritas penanganan jalan di Kabupaten Badung.

Landfill site selection using multi criteria decision making: Influential factors for comparing locations

Appropriate tree fertilization with essential nutrients is considered as one of the major factors in enhancing the quality and quantity of horticultural crops. The most efficient way to fertilize trees is to dig holes around the trunks and fill them with appropriate chemical and organic fertilizer. Doing this operation with mechanized methods reduces costs and increases productivity compared to traditional methods. In the present study, multi‐criteria decision‐making (MCDM) methods, including deterministic analytical hierarchy process (AHP) and fuzzy analytical hierarchy process (FAHP), technique for order of preference by similarity to ideal solution (TOPSIS), fuzzy TOPSIS (FTOPSIS), and analytic network process (ANP), were used to score and select the appropriate fertilizing method for apple trees based on the growers and expert's perspectives. The criteria, including fertilizing operation cost, crop yield, the percentage of tree damages, ease of entering and moving fertilizing equipment in tree rows, field capacity (with or without machinery), comfort and safety of fertilizing operations, after‐sales service, access to the required machinery and implements, crop selling price, and crop quality, were used in the above‐mentioned methods. The fertilization methods (Hole digging) considered in the present study were traditional fertilization (Shovel), orchard Trencher, motor hole digger, fixed centerline tractor‐mounted hole digger, and off‐set tractor‐mounted hole digger. Based on the results, the priority of mechanized fertilizing methods was determined as tractor‐mounted hole diggers (AHP weight of 0.286, FAHP weight of 0.285, TOPSIS relative proximity of 0.65, and FTOPSIS relative proximity of 0.64), fixed centerline tractor‐mounted hole diggers (AHP weight of 0.219, FAHP weight of 0.158, TOPSIS relative proximity of 0.56, and FTOPSIS relative proximity of 0.62), motor hole diggers (AHP weight of 0.171, FAHP weight of 0.079, TOPSIS relative proximity of 0.46, and FTOPSIS relative proximity of 0.31), and orchard trenchers (AHP weight of 0.12, FAHP weight of 0.057, TOPSIS relative proximity of 0.19, and FTOPSIS relative proximity of 0.20), respectively. Based on the ANP method, off‐set and fixed centerline tractor‐mounted hole diggers had the highest priority (weights of 0.43 and 0.27), followed by trencher (weight of 0.16), motor hole diggers (weight of 0.09), and the traditional method (weight of 0.04). Results showed that applying orchard tractors equipped with mounted diggers, especially off‐set types, can play an important role in enhancing the quantity and quality of apples produced, as well as reducing the costs of fertilizing operations.

Identification of influential nodes has emerged as one of the major challenges, especially after their use in the rapid propagation of information, epidemics, and so on in social media. Most of the previous works in this field deal with the homogeneous interactions that are not pertinent in the determination of the accurate context of the nodes due to their noisy and sparse nature. Hence, heterogeneous interactions need to be explored for the identification of influential nodes in the network. To consider heterogeneous interactions available within the network, a multilayer network (ML) has been designed in this work. Each layer of the network represents a particular type of interaction, e.g., upload, comment, retweet, reply, and mention. A heterogeneous degree ranking (HDR)-based influential nodes’ detection and ranking are proposed for the designed ML. Furthermore, multiple-criteria decision-making (MCDM) methods, such as the analytic hierarchy process (AHP), the technique for order of preference by similarity to ideal solution (TOPSIS), fuzzy AHP, fuzzy TOPSIS, and the analytic network process (ANP), are explored for the proposed ML for identification and ranking of the influential nodes. The susceptible–infected–recovered (SIR) model is used to evaluate the proposed work. In addition to this, statistical analysis is performed using the Pearson correlation, Kendall’s correlation, Spearman’s correlation, and the Friedman test on the ranks generated by different methods, which shows that the results generated by different proposed methods are consistent. Furthermore, the performance of the proposed method is compared with state-of-the-art approaches.

Employee selection is one of the essential functions of human resource management. The main aim of the paper is to analyse the application of multiple criteria decision-making (MCDM) methods in the process of the employee recruitment process to establish frameworks that help accepting best decisions. Information about the candidates, which was acquired by managers during various kinds of testing and personal interviews at the assessment centre, constitutes the input data of our research. Subsequently, this information was processed and analysed using two of the most popular MCDM methods - the analytic hierarchy process (AHP) and the analytic network process (ANP). These were chosen because of their versatility and high efficiency in solving various types of decision-making problems. Finally, we compared the outcomes obtained by both methods. We discuss their potential for practical use. The application of AHP seems to be preferable for this group of problems because of its simplicity, and because less information is required from decision-makers.

An improved MCDM combined with GIS for risk assessment of multi-hazards in Hong Kong

In this study, an intelligent approach is presented to help any simulation practitioner to evaluate simulation software alternatives and determine the best satisfying one based on his/her needs. On the other hand, this evaluation process is a typical multiple criteria decision making (MCDM) problem in the presence of evaluation criteria and a set of possible alternatives, and there are many methods in the literature, which have been used to successfully carry out this difficult and time-consuming process. In this paper, one of these methods, the analytic network process (ANP) method integrated with alpha-cut fuzzy logic is used because it can accommodate the variety of interactions, dependencies and feedback between higher and lower level elements, rather than analytic hierarchy process (AHP). In addition, an alpha-cut fuzzy extension of ANP uses uncertain human preferences as input information in the decision-making process. Instead of using the classical eigenvector prioritisation method in AHP, only employed in the prioritisation stage of ANP, an alpha-cut fuzzy logic method providing more accuracy on judgements is applied. The resulting alpha-cut fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgements.

Previous researches outlined the advantages of the Analytical Hierarchy Process (AHP) and Analytic Network Process (ANP) methods in solving Multi-Attribute Decision Making (MADM) problems. The advancement of the above methods was continually developed as an effort to cover up various weaknesses. Mainly related to the consistency and linguistic variables in translating the expert opinions. Thus, it initialized the emergence of Fuzzy AHP (F-AHP) and Fuzzy ANP (F-ANP). Due to the restricted operation of these algorithms in smartphone selection, this research attempted to investigate the effectiveness of both methods in providing the analysis of criteria weight, the final recommendation weight, the product recommendation weight, and the execution time in DSS-SmartPhoneRec application development. A survey of one hundred respondents of University students identified the dominant criteria in selecting the smartphone, namely price, Random Access Memory (RAM), processor, internal memory, and camera. Hence, five alternative products were then chosen as the appropriate smartphones’ recommendations based on the respondent’s preferences. As an automatic tool, a DSS-SmartPhoneRec application was built to analyze and compare between F-AHP and F-ANP methods in resolving the smartphone selection cases. It revealed that the level of consistency of criteria weight, the final weight of recommendation, and the weight that the product-based F-ANP was 40% greater than F-AHP. In terms of execution time, F-AHP had a shorter time than F-ANP. Meanwhile, the comparison of products recommendation from DSS-SmartPhoneRec and a manual test showed that F-ANP was 16% more in line with the respondents’ predilection. In a nutshell, the DSS-SmartPhoneRec administered the devote smartphone recommendations based on the user’s expectation. The comparison analysis furnished a learning outcome for the users in determining the appropriate MADM method tailored to the type of cases.

Evaluating the system intelligence of the intelligent building systems: Part 2: Construction and validation of analytical models

The government's limited budget in managing the condition of the road pavement causes the government to compile a priority ranking of the roads to be handled. Each decision maker has a different assessment for each factor or criterion that is considered in determining the path. This problem requires the same perception from decision makers in choosing road handling priorities. Priority by determining more than one criteria can be done using Multi Criteria Decision Making (MCDM) analysis such as Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP). This study seeks to obtain priority handling of the Jalan Bts. Tapteng/Tapsel – Batang Toru – Bts. Sidempuan City using AHP and ANP methods. The criteria used are traffic volume, level of road damage, government policies, handling costs, and area development. The segmentation of the road segment is applied in this study into 9 sub-sections to obtain a uniform alternative length of the road. The results show that the most influential criteria in road handling using the AHP method are traffic volume (0.428), followed by policy (0.192), cost (0.187), road conditions (0.141), and area development (0.052). While in the ANP method, the criteria with the largest weight are traffic volume (0.301), followed by policies (0.196), costs (0.194), road conditions (0.174), and area development (0.134). The results of the two methods also determine the priority of different road handling roads. The results of the ANP method are expected to be a more objective priority due to the consideration of feedback on the elements and clusters themselves.

The present study provides a comparative analysis of development strategy selection and presents an overview of multiple-criteria decision analysis (MCDA) in strategic management. The main aim of the paper is to use the analytic network process (ANP) as one of MCDA methods for determining the best strategy. Based on expert opinions and analytic hierarchy process (AHP), the authors have identified and evaluated SWOT analysis factors used for the development of a company strategy. To investi-gate the interaction of external and internal environment, the authors have used the ANP that allows obtaining relative measurement of the influence of SWOT elements. The ANP is useful with regard to interdependent relationship between multi-objectives and multi-stakeholders’ environment. The algo-rithm of quantitative evaluation of telecommunication company strategies is also presented in the paper.

Watershed prioritization using morphometric analysis by MCDM approaches

Online and blended learning requires the reconstruction of instructor and learner roles, relations, and practices in many aspects. Assessment becomes an important issue in non-traditional learning environments. Assessment literacy, i.e., understanding assessment and assessment strategies, is critical for both instructors and students in creating online and blended environments that are effective for teaching and learning. Instructors need to identify and implement assessment strategies and methods appropriate to online or blended learning. This includes an understanding of the potential of a variety of technology tools for monitoring student learning and improving their teaching effectiveness. From the students’ perspective, good assessment practices can show them what is important to learn and how they should approach learning; hence, engaging them in goal-oriented and self-regulatory cognitions and behaviors.The book targets instructors, instructional designers, and educational leaders who are interested in understanding and implementing either summative or formative assessment in online and blended learning environments. This book will assist the relevant audience in the theory and practice of assessment in online and blended learning environments. Providing both a research and practice perspective, this book can help instructors make the connection between pedagogy and technology tools to maximize their teaching and student learning. Among the questions addressed in this book are:• What assessment strategies can be used in online or blended learning?• How can instructors design effective assessment strategies?• What methods or technology tools can be used for assessment in online or blended learning?• How does peer-assessment work in online or blended learning environments?

Given the growing competition in domestic and international agricultural product markets, choosing a business strategy compatible with requirements of marketing resources can guide agro-food firms to maintain and enhance competitive advantages. However, this is not as simple as it seems because the decision-making criteria expressed in a fuzzy manner and the relationship between them can be hierarchical or network-based. Therefore, the main goal of this study was to select the most suitable business strategy and to prioritize marketing resources for one of the major agro-food firms in Iran. To ensure the robustness of the results, both fuzzy analytic hierarchy process (AHP) and fuzzy analytic network process (ANP) were applied to prioritize business strategies and marketing resources. The results of both methods revealed that the differentiation strategy had the highest priority in terms of the experts' viewpoints. The results also showed that managerial and customer relationship capabilities were the most important criteria in selecting the differentiation strategy. According to the findings of the study, for the successful implementation of the differentiation strategy, company managers are recommended to take the following three main elements into huge consideration: financial conditions, paying attention to customer’s needs and requirements, and the introduction of new products and services.

The ongoing water deficiencies in arid and semi-arid regions in conjunction with certain nutritional requirements highlight the importance of pinpointing the most optimal locations for cultivating agricultural products with the highest yield. Given the importance of this issue, this study proceeds to prepare soil fertility maps for corn production (Zea Mays L.) in Fars province, Iran. Initially, fuzzy membership functions (FMs) are employed to prepare fuzzy maps for each layer in the geographic information system (GIS), after which feature selection algorithms are deployed to designate the most relevant layers. The layers are then assigned specific weights obtained using a combination of analytic network process (ANP) and analytic hierarchy process (AHP) methods to prepare soil fertility maps. The input data consist of organic content (OC), phosphorus (P), potassium (K), iron (Fe), zinc (Zn), manganese (Mn), and copper (Cu). Inverse distance weighting (IDW) is utilized to procure interpolation maps for each layer. Thereafter, zoning maps are obtained using FMs. Ultimately, ANP and AHP models are once again deployed to generate the final overlayered fertility maps for corn production. The results show that combining the ANP method with feature selection (OC, K, Fe, and P) results in higher accuracy than solely applying the AHP method. Thus, incorporating feature selection and ANP methods with both inter and intra-group pair-wise comparison would result in more accurate fertility maps for corn production with lower costs and time complexity.