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1 – 10 of 297
Article
Publication date: 19 March 2024

Thao-Trang Huynh-Cam, Long-Sheng Chen and Tzu-Chuen Lu

This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct…

Abstract

Purpose

This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability.

Design/methodology/approach

The real-world samples comprised the enrolled records of 2,412 first-year students of a private university (UNI) in Taiwan. This work utilized decision trees (DT), multilayer perceptron (MLP) and logistic regression (LR) algorithms for constructing EPMs; under-sampling, random oversampling and synthetic minority over sampling technique (SMOTE) methods for solving data imbalance problems; accuracy, precision, recall, F1-score, receiver operator characteristic (ROC) curve and area under ROC curve (AUC) for evaluating constructed EPMs.

Findings

DT outperformed MLP and LR with accuracy (97.59%), precision (98%), recall (97%), F1_score (97%), and ROC-AUC (98%). The top-ranking factors comprised “student loan,” “dad occupations,” “mom educational level,” “department,” “mom occupations,” “admission type,” “school fee waiver” and “main sources of living.”

Practical implications

This work only used enrollment information to identify dropout students and crucial factors associated with dropout probability as soon as students enter universities. The extracted rules could be utilized to enhance student retention.

Originality/value

Although first-year student dropouts have gained non-stop attention from researchers in educational practices and theories worldwide, diverse previous studies utilized while-and/or post-semester factors, and/or questionnaires for predicting. These methods failed to offer universities early warning systems (EWS) and/or assist them in providing in-time assistance to dropouts, who face economic difficulties. This work provided universities with an EWS and extracted rules for early dropout prevention and intervention.

Details

Journal of Applied Research in Higher Education, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-7003

Keywords

Open Access
Article
Publication date: 18 March 2024

Alesandra de Araújo Benevides, Alan Oliveira Sousa, Daniel Tomaz de Sousa and Francisca Zilania Mariano

Adolescent pregnancy stands as a societal challenge, compelling young individuals to prematurely discontinue their education. Conversely, an expansion of high school education can…

Abstract

Purpose

Adolescent pregnancy stands as a societal challenge, compelling young individuals to prematurely discontinue their education. Conversely, an expansion of high school education can potentially diminish rates of adolescent pregnancy, given that educational attainment stands as the foremost risk factor influencing sexual initiation, the use of contraceptive methods during initial sexual encounters and fertility. The aim of this paper is to analyze the impact of the implementation of the public educational policy introducing full-time schools (FTS) for high schools in the state of Ceará, Brazil, on early pregnancy rates.

Design/methodology/approach

Using the difference-in-differences method with multiple time periods, we measured the average effect of this staggered treatment on the treated municipalities.

Findings

The main result indicates a reduction of 0.849 percentage points in the teenage pregnancy rate. Concerning dynamic effects, the establishment of FTS in treated municipalities results in a 1.183–1.953 percentage point decrease in teenage pregnancy rates, depending on the timing of exposure. We explored heterogeneous effects within socioeconomically vulnerable municipalities, yet discerned no impact on this group. Rigorous tests confirm the robustness of the results.

Originality/value

This paper aims to contribute to: (1) the consolidation of research on the subject, given the absence of such research in Brazil to the best of our knowledge; (2) the advancement and analysis of evidence-based public policy and (3) the utilization of novel longitudinal data and methodology to evaluate adolescent pregnancy rates.

Details

EconomiA, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1517-7580

Keywords

Book part
Publication date: 25 October 2023

Dritero Arifi and Ngadhnjim Brovina

This chapter delves into the education of Kosovo's Roma community, shining a light on the obstacles they encounter and the initiatives taken by the government to enhance their…

Abstract

This chapter delves into the education of Kosovo's Roma community, shining a light on the obstacles they encounter and the initiatives taken by the government to enhance their educational prospects. The Roma community represents just 0.5% of Kosovo's entire population and faces significant challenges with low literacy rates and high dropout rates, particularly at lower levels of education. Since Kosovo's independence proclamation in 2008, there have been institutional advancements and partnerships with local, central, and worldwide organisations to improve the education system for the Roma community.

This study aims to provide an in-depth understanding of the educational situation of the Roma community in Kosovo. It recognises their challenges and proposes practical solutions to accelerate their integration and improve their social, educational, and cultural welfare. Various analytical methods, including descriptive statistics and historical analysis, are utilised to conduct comparative and quantitative assessments.

The Roma community in Kosovo continues to encounter numerous challenges, such as economic hardships, lack of education opportunities, and early marriages that often result in school dropouts. However, research highlights the government's dedication to enhancing education conditions and enabling better access to the labour market for the Roma community through proper education and qualifications. Additionally, Kosovo's constitutional and legal framework safeguards the rights of all communities, including the Roma community, regarding education and employment with high standards.

Details

Lifelong Learning and the Roma Minority in the Western Balkans
Type: Book
ISBN: 978-1-80382-522-9

Keywords

Article
Publication date: 20 October 2023

Elizabeth Lapon and Leslie Buddington

The transition to college presents significant challenges for many students as they navigate new academic and social experiences. In the USA, 30% of first-year students drop out…

Abstract

Purpose

The transition to college presents significant challenges for many students as they navigate new academic and social experiences. In the USA, 30% of first-year students drop out before their second year. Research indicates that mentoring programs help students achieve social integration and likely have a positive effect on their transition to college. This research study was conducted with education students to better understand the potential impacts of peer mentorship.

Design/methodology/approach

Student mentors and mentees were matched by attributes such as their concentration within the education major, gender, sports they played and whether they were first-generation matriculants. Data collection utilized two surveys one before the peer mentoring process and one after the process.

Findings

The findings suggest that peer mentoring improved first-generation students' sense of belonging to both their major and the college. Peer mentors also experienced increased belongingness. The transfer rate among participants of 2% was a significant drop from previous years.

Originality/value

The success of the peer mentoring experience was possibly due to the intentional matching process based on certain attributes. Additionally, taking a leadership role increased a sense of belonging in the peer mentors.

Details

International Journal of Mentoring and Coaching in Education, vol. 13 no. 1
Type: Research Article
ISSN: 2046-6854

Keywords

Article
Publication date: 28 March 2023

Dmitri Williams, Sukyoung Choi, Paul L. Sparks and Joo-Wha Hong

The study aims to determine the outcomes of mentorship in an online game system, as well as the characteristics of good mentors.

Abstract

Purpose

The study aims to determine the outcomes of mentorship in an online game system, as well as the characteristics of good mentors.

Design/methodology/approach

A combination of anonymized survey measures and in-game behavioral measures were used to power longitudinal analysis over an 11-month period in which protégés and non-mentored new players could be compared for their performance, social connections and retention.

Findings

Successful people were more likely to mentor others, and mentors increased protégés' skill. Protégés had significantly better retention, were more active and much more successful as players than non-protégés. Contrary to expectations, younger, less wealthy and educated people were more likely to be mentors and mentors did not transfer their longevity. Many of the qualities of the mentor remain largely irrelevant—what mattered most was the time spent together.

Research limitations/implications

This is a study of an online game, which has unknown generalizability to other games and to offline settings.

Practical implications

The results show that getting mentors to spend dedicated time with protégés matters more than their characteristics.

Social implications

Good mentorship does not require age or resources to provide real benefits.

Originality/value

This is the first study of mentorship to use survey and objective outcome measures together, over time, online.

Details

Internet Research, vol. 34 no. 2
Type: Research Article
ISSN: 1066-2243

Keywords

Abstract

Details

Teacher Preparation in Papua New Guinea
Type: Book
ISBN: 978-1-83549-077-8

Article
Publication date: 30 January 2023

Zhongbao Liu and Wenjuan Zhao

In recent years, Chinese sentiment analysis has made great progress, but the characteristics of the language itself and downstream task requirements were not explored thoroughly…

Abstract

Purpose

In recent years, Chinese sentiment analysis has made great progress, but the characteristics of the language itself and downstream task requirements were not explored thoroughly. It is not practical to directly migrate achievements obtained in English sentiment analysis to the analysis of Chinese because of the huge difference between the two languages.

Design/methodology/approach

In view of the particularity of Chinese text and the requirement of sentiment analysis, a Chinese sentiment analysis model integrating multi-granularity semantic features is proposed in this paper. This model introduces the radical and part-of-speech features based on the character and word features, with the application of bidirectional long short-term memory, attention mechanism and recurrent convolutional neural network.

Findings

The comparative experiments showed that the F1 values of this model reaches 88.28 and 84.80 per cent on the man-made dataset and the NLPECC dataset, respectively. Meanwhile, an ablation experiment was conducted to verify the effectiveness of attention mechanism, part of speech, radical, character and word factors in Chinese sentiment analysis. The performance of the proposed model exceeds that of existing models to some extent.

Originality/value

The academic contribution of this paper is as follows: first, in view of the particularity of Chinese texts and the requirement of sentiment analysis, this paper focuses on solving the deficiency problem of Chinese sentiment analysis under the big data context. Second, this paper borrows ideas from multiple interdisciplinary frontier theories and methods, such as information science, linguistics and artificial intelligence, which makes it innovative and comprehensive. Finally, this paper deeply integrates multi-granularity semantic features such as character, word, radical and part of speech, which further complements the theoretical framework and method system of Chinese sentiment analysis.

Details

Data Technologies and Applications, vol. 57 no. 4
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 29 December 2023

B. Vasavi, P. Dileep and Ulligaddala Srinivasarao

Aspect-based sentiment analysis (ASA) is a task of sentiment analysis that requires predicting aspect sentiment polarity for a given sentence. Many traditional techniques use…

Abstract

Purpose

Aspect-based sentiment analysis (ASA) is a task of sentiment analysis that requires predicting aspect sentiment polarity for a given sentence. Many traditional techniques use graph-based mechanisms, which reduce prediction accuracy and introduce large amounts of noise. The other problem with graph-based mechanisms is that for some context words, the feelings change depending on the aspect, and therefore it is impossible to draw conclusions on their own. ASA is challenging because a given sentence can reveal complicated feelings about multiple aspects.

Design/methodology/approach

This research proposed an optimized attention-based DL model known as optimized aspect and self-attention aware long short-term memory for target-based semantic analysis (OAS-LSTM-TSA). The proposed model goes through three phases: preprocessing, aspect extraction and classification. Aspect extraction is done using a double-layered convolutional neural network (DL-CNN). The optimized aspect and self-attention embedded LSTM (OAS-LSTM) is used to classify aspect sentiment into three classes: positive, neutral and negative.

Findings

To detect and classify sentiment polarity of the aspect using the optimized aspect and self-attention embedded LSTM (OAS-LSTM) model. The results of the proposed method revealed that it achieves a high accuracy of 95.3 per cent for the restaurant dataset and 96.7 per cent for the laptop dataset.

Originality/value

The novelty of the research work is the addition of two effective attention layers in the network model, loss function reduction and accuracy enhancement, using a recent efficient optimization algorithm. The loss function in OAS-LSTM is minimized using the adaptive pelican optimization algorithm, thus increasing the accuracy rate. The performance of the proposed method is validated on four real-time datasets, Rest14, Lap14, Rest15 and Rest16, for various performance metrics.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 31 August 2023

Helena Á Marujo

This underscores individual and social implications for how mental disorders and mental well-being are constructed, conceived of and treated. Further, this paper aims to examine…

Abstract

Purpose

This underscores individual and social implications for how mental disorders and mental well-being are constructed, conceived of and treated. Further, this paper aims to examine positive psychology’s role in supporting the advancement of a broader systemic and contextual approach to mental health. With that aim, this paper connects data on mental health and well-being with peace studies to describe the systems of value and social ecologies underpinning mental disorders, using public happiness/Felicitas Publica as a possible framework to enhance public mental health while intervening at the local level (Bruni and Zamagni, 2007; Marujo and Neto, 2013, 2014, 2016, 2017, 2021; Marujo et al., 2019).

Design/methodology/approach

Theoretical foundations and data on positive peace and mental well-being are described with the intention to propose a systemic, contextual, relational, communitarian, economic and sociopolitical perspective of well-being that goes beyond individual bodies and/or brains and, instead, views mental disorder and mental health as social currency (Beck, 2020).

Findings

The interventions using dialogic, conversational and community approaches are a possible path to promote peace, mental health and public happiness.

Research limitations/implications

Examining the interplay between the fields of positive psychology, mental health and cultures of peace, this work contributes to the broadening of research and subsequent intervention topics through transdisciplinary approaches while reinforcing the role of systemic and social determinants and complementing the prevalent medical model and intraindividual perspective of mental health and well-being.

Practical implications

Adopting positive psychology to address mental health through public happiness concepts and interventions opens opportunities to respond to the ebb and flow of social challenges and life-giving opportunities. Therefore, the paper intends to articulate actor-related, relational, structural and cultural dimensions while moving away from discrete technocratic and individual models and pays attention to the way their implementations are aligned with both individual and social needs.

Social implications

The work offers an inclusive, equalitarian, politically sensitive approach to positive mental health and positive psychology, bringing forward a structural transformation and human rights-based approach perspective while rethinking the type of social and political solutions to mental health issues.

Originality/value

Creating a critically constructive debate vis-à-vis the fluidity and complexity of the social world, the paper examines mental health and positive psychology simultaneously from a “hardware” (institutions, infrastructures, services, systems, etc.) and a “software” (i.e. individuals and community/societal relations).

Details

Mental Health and Social Inclusion, vol. 27 no. 4
Type: Research Article
ISSN: 2042-8308

Keywords

Article
Publication date: 14 November 2023

Shaodan Sun, Jun Deng and Xugong Qin

This paper aims to amplify the retrieval and utilization of historical newspapers through the application of semantic organization, all from the vantage point of a fine-grained…

Abstract

Purpose

This paper aims to amplify the retrieval and utilization of historical newspapers through the application of semantic organization, all from the vantage point of a fine-grained knowledge element perspective. This endeavor seeks to unlock the latent value embedded within newspaper contents while simultaneously furnishing invaluable guidance within methodological paradigms for research in the humanities domain.

Design/methodology/approach

According to the semantic organization process and knowledge element concept, this study proposes a holistic framework, including four pivotal stages: knowledge element description, extraction, association and application. Initially, a semantic description model dedicated to knowledge elements is devised. Subsequently, harnessing the advanced deep learning techniques, the study delves into the realm of entity recognition and relationship extraction. These techniques are instrumental in identifying entities within the historical newspaper contents and capturing the interdependencies that exist among them. Finally, an online platform based on Flask is developed to enable the recognition of entities and relationships within historical newspapers.

Findings

This article utilized the Shengjing Times·Changchun Compilation as the datasets for describing, extracting, associating and applying newspapers contents. Regarding knowledge element extraction, the BERT + BS consistently outperforms Bi-LSTM, CRF++ and even BERT in terms of Recall and F1 scores, making it a favorable choice for entity recognition in this context. Particularly noteworthy is the Bi-LSTM-Pro model, which stands out with the highest scores across all metrics, notably achieving an exceptional F1 score in knowledge element relationship recognition.

Originality/value

Historical newspapers transcend their status as mere artifacts, evolving into invaluable reservoirs safeguarding the societal and historical memory. Through semantic organization from a fine-grained knowledge element perspective, it can facilitate semantic retrieval, semantic association, information visualization and knowledge discovery services for historical newspapers. In practice, it can empower researchers to unearth profound insights within the historical and cultural context, broadening the landscape of digital humanities research and practical applications.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

1 – 10 of 297