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Although educators would likely agree that values and ethics are important in all disciplines, they have particular importance for practice-oriented fields. These applied professionals need to solve complex social problems that require the application of ethical standards and value perspectives. While the importance of value-engaged practice is known to the applied field, there is little research and conversation about how values can be integrated into teaching. This chapter synthesizes values-education approaches in various practice-based disciplines such as public administration (PA), program evaluation, social work, and public health. This chapter draws from empirical and theoretical works as well as the authors' experiences developing, participating in, and conducting values-based research on professionals and professional education.

As global issues such as climate change, economic growth, social equality and the wealth gap are widely discussed, education for sustainable development (ESD) allows every human being to acquire the knowledge, skills, attitudes and values necessary to shape a sustainable future. It also requires participatory teaching and learning methods that motivate and empower learners to change their behavior and take action for sustainable development. Teachers have begun rating pupils based on peer assessment for open evaluation. Peer assessment enables students to transition from passive to active feedback recipients. The assessors improve critical thinking and encourage introspection, resulting in more significant recommendations. However, the quality of peer assessment is variable, resulting in reviewers not recognizing the remarks of other reviewers, therefore the benefits of peer assessment cannot be fulfilled. In the past, researchers frequently employed post-event questionnaires to examine the effects of peer assessment on learning effectiveness, which did not accurately reflect the quality of peer assessment in real time.

This study employs a multi-label model and develops a self-feedback system in order to use the AIOLPA system in the classroom to enhance students' learning efficacy and the validity of peer assessment.

The research findings indicate that the better peer assessment through the rapid feedback system, for the evaluator, encourages more self-reflection and attempts to provide more ideas, so bringing the peer rating closer to the instructor rating and assisting the evaluator. Improve self-evaluation and critical thinking for the evaluator, peers make suggestions and comments to help improve the work and support the growth of students' learning effectiveness, which can lead to more suggestions and an increase in the work’s quality.

ESD consequently promotes competencies like critical thinking, imagining future scenarios and making decisions in a collaborative way. This study builds an online peer assessment system with a self-feedback mechanism capable of classifying peer comments, comparing them with scores in a consistent manner and providing prompt feedback to critics.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

During the evaluation of European Capital of Culture (ECoC) Aarhus 2017, the evaluation organisation rethinkIMPACTS 2017 formulated a set of “dilemmas” capturing the main challenges arising during the design of the ECoC evaluation. This functioned as a framework for the evaluation process. This paper aims to present and discuss the relevance of the “Evaluation Dilemmas Model” as subsequently applied to the Galway 2020 ECoC programme evaluation.

The paper takes an empirical approach including auto-ethnography and interview data to document and map the dilemmas involved in undertaking an evaluation in two different European cities. Evolved via a process of practice-based research, the article addresses the development of and the arguments for the dilemmas model and considers its potential for wider applicability in the evaluation of large-scale cultural projects.

The authors conclude that the “Evaluation Dilemmas Model” is a valuable heuristic for considering the endogenous and exogenous issues in cultural evaluation.

The model developed is useful for a wide range of cultural evaluation processes including – but not limited to – European Capitals of Culture.

What has not been addressed in the academic literature is the process of evaluating ECoCs; especially how evaluators often take part in an overall process that is not just about the evaluation but also planning and delivering a project that includes stakeholder management and the development of evaluation criteria, design and methods.

The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.

Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.

ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.

This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.

This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

Users often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.

In this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users’ credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.

Theoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.

The proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.

Understanding the multifaceted images of tourism destinations is critical for effective destination marketing and management strategies. Traditional approaches, including conceptualization of destination images or analysis of their antecedents and consequences, are commonly used. This study aims to advocate the inclusion of visitors’ latent profiles based on cognitive images to enrich the evaluation and formulation of destination marketing and management strategies.

The analysis focuses on Serbia, an emerging destination, that attracts an increasing number of first-time, repeat and prospective visitors. Exploratory factor analysis and confirmatory factor analysis were used to test the potential dimensions (tangible and intangible cultural destination; infrastructural and accessible destination; active, nature and family destination; sensory and hospitable destination; and welcoming, value for money (VFM) and safe destination) of the cognitive destination image factors scale while subtypes (profiles) were obtained using latent profile analysis (LPA).

The cognitive image component encompasses the perceived attributes of a destination, whether derived from direct experience or acquired through other means. The study identified the following profiles: conventional destination; sensory and hospitable destination; welcoming, VFM and safe destination; secure and active family destination and accessible cultural destination, which are presented individually with their sociodemographic assets.

The main contribution of the paper is the application of a novel method (LPA) for profiling visitor segments based on cognitive destination image. From a theoretical perspective, this research contributes to the extant body of literature pertaining to the destination image, thereby facilitating the identification of discrete latent visitor segments and elucidating noteworthy differences among them concerning a cognitive image.

The purpose of this study is to examine the impact of educational service quality (ESQ) on student academic performance via the mediating role of student satisfaction.

To serve the study’s purpose, the study adopted a quantitative research approach. Three public universities representing 30% of the ten public universities located in the Southern part of Ethiopia participated in the study. Questionnaires were the main tools for gathering data. The adapted questionnaire, consisting of 116 items was administered to 400 randomly selected regular undergraduate graduating class students. The quantitative data collected via questionnaire were analyzed using descriptive and advanced inferential statistics.

The quantitative findings revealed that there is a statistically positive association between overall education service quality and students’ satisfaction (r = 0.712). The findings proved that the facets of education service quality accounted for 71.2% of the variations in students’ satisfaction in the universities. The quantitative findings further showed that the education service quality has a statistically indirect effect on students’ academic performance via the mediating role of students’ satisfaction (test statistic = 31.5311573, std. error = 0.00122536 and p-value = 0). The findings further confirmed that the overall education service quality accounted for 12.7% of the variations in students’ academic performance via student satisfaction in the universities.

The present study was conducted in public universities located in the Southern part of Ethiopia. The findings and conclusions of the study may not be generalizable to all Ethiopian public universities. Future researchers and scholars should conduct their study in all Ethiopian public universities by taking a representative sample from the Ethiopian public universities.

The present finding suggests that an improvement in ESQ leads to students’ satisfaction and that could contribute to boosting their academic performance. The findings of the present may help the practitioners who measure higher education service quality by providing how the provision of ESQ indirectly influences the student’s academic performance in the universities.

The findings of this study confirmed that the facets of ESQ are associated with students’ satisfaction and this, in turn, indirectly influences their academic performance. Student academic performance is one of the key indicators of quality education, and it has its influences on the social, political and economic development of a country. The findings of the present research provide valuable insights to higher education management bodies, higher quality assurance agencies and the Federal Ministry of Education to learn the indirect effect of ESQ on students’ academic performance and take necessary measures to improve the Ethiopian higher education quality.

The contributions of ESQ in the higher education sector are enormous. However, the existing service quality literature in higher education mainly focuses on the interrelation among service quality, student satisfaction, loyalty and behavioral intentions. Little is known about the indirect influence of ESQ on student academic performance (one of the key indicators of quality education), principally in Ethiopian higher education, the place of current research. The present study showed the indirect impact of ESQ on student academic performance in Ethiopian public universities. The study, therefore, suggests that university management bodies should actively monitor the quality of their services and commit themselves to boosting students’ learning outcomes.