PeerJ Computer Science最新文献

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Automatic generation of explanations in autonomous systems: enhancing human interaction in smart home environments. 自主系统中的自动生成解释:增强智能家居环境中的人类互动。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-29 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3041
Oscar Peña-Cáceres, Antoni Mestre, Manoli Albert, Vicente Pelechano, Miriam Gil
{"title":"Automatic generation of explanations in autonomous systems: enhancing human interaction in smart home environments.","authors":"Oscar Peña-Cáceres, Antoni Mestre, Manoli Albert, Vicente Pelechano, Miriam Gil","doi":"10.7717/peerj-cs.3041","DOIUrl":"https://doi.org/10.7717/peerj-cs.3041","url":null,"abstract":"<p><p>In smart environments, autonomous systems often adapt their behavior to the context, and although such adaptations are generally beneficial, they may cause users to struggle to understand or trust them. To address this, we propose an explanation generation system that produces natural language descriptions (explanations) to clarify the adaptive behavior of smart home systems in runtime. These explanations are customized based on user characteristics and the contextual information derived from the user interactions with the system. Our approach leverages a prompt-based strategy using a fine-tuned large language model, guided by a modular template that integrates key data such as the type of explanation to be generated, user profile, runtime system information, interaction history, and the specific nature of the system adaptation. As a preliminary step, we also present a conceptual model that characterize explanations in the domain of autonomous systems by defining their core concepts. Finally, we evaluate the user experience of the generated explanations through an experiment involving 118 participants. Results show that generated explanations are perceived positive and with high level of acceptance.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3041"},"PeriodicalIF":2.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453768/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The DBCV index is more informative than DCSI, CDbw, and VIASCKDE indices for unsupervised clustering internal assessment of concave-shaped and density-based clusters. 对于凹形和基于密度的聚类的无监督聚类内部评估,DBCV指数比DCSI、CDbw和VIASCKDE指数信息更丰富。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-29 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3095
Davide Chicco, Giuseppe Sabino, Luca Oneto, Giuseppe Jurman
{"title":"The DBCV index is more informative than DCSI, CDbw, and VIASCKDE indices for unsupervised clustering internal assessment of concave-shaped and density-based clusters.","authors":"Davide Chicco, Giuseppe Sabino, Luca Oneto, Giuseppe Jurman","doi":"10.7717/peerj-cs.3095","DOIUrl":"10.7717/peerj-cs.3095","url":null,"abstract":"<p><p>Clustering methods are unsupervised machine learning techniques that aggregate data points into specific groups, called <i>clusters</i>, according to specific criteria defined by the clustering algorithm employed. Since clustering methods are unsupervised, no ground truth or gold standard information is available to assess its results, making it challenging to know the results obtained are good or not. In this context, several clustering internal rates are available, like Silhouette coefficient, Calinski-Harabasz index, Davies-Bouldin, Dunn index, Gap statistic, and Shannon entropy, just to mention a few. Even if popular, these clustering internal scores work well only when used to assess convex-shaped and well-separated clusters, but they fail when utilized to evaluate concave-shaped and nested clusters. In these concave-shaped and density-based cases, other coefficients can be informative: Density-Based Clustering Validation Index (DBCVI), Compose Density between and within clusters Index (CDbw), Density Cluster Separability Index (DCSI), Validity Index for Arbitrary-Shaped Clusters based on the kernel density estimation (VIASCKDE). In this study, we describe the DBCV index precisely, and compare its outcomes with the outcomes obtained by CDbw, DCSI, and VIASCKDE on several artificial datasets and on real-world medical datasets derived from electronic health records, produced by density-based clustering methods such as density-based spatial clustering of applications with noise (DBSCAN). To do so, we propose an innovative approach based on clustering result worsening or improving, rather than focusing on searching the \"right\" number of clusters like many studies do. Moreover, we also recommend open software packages in R and Python for its usage. Our results demonstrate the higher reliability of the DBCV index over CDbw, DCSI, and VIASCKDE when assessing concave-shaped, nested, clustering results.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3095"},"PeriodicalIF":2.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453699/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Delegated multi-party private set intersections from extendable output functions. 可扩展输出函数的委托多方私有集交集。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-29 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3141
Aslı Bay
{"title":"Delegated multi-party private set intersections from extendable output functions.","authors":"Aslı Bay","doi":"10.7717/peerj-cs.3141","DOIUrl":"10.7717/peerj-cs.3141","url":null,"abstract":"<p><p>Operations on sensitive datasets from different parties are essential for various practical applications, such as verifying shopping lists or enforcing no-fly lists. Traditional methods often require one party to access both datasets, which poses privacy concerns. Private set operations provide a solution by enabling these functions without revealing the data involved. However, protocols involving three or more parties are generally much slower than unsecured methods. Outsourced private set operations, where computations are delegated to a non-colluding server, can significantly improve performance, though current protocols have not fully leveraged this assumption. We propose a new protocol that removes the need for public-key cryptography. Our non-interactive set intersection protocol relies solely on the security of an extendable output function, achieving high efficiency. Even in a ten-client setting with 16,384-element sets, the intersection can be computed in under 54 s without communication overhead. Our results indicate that substantial performance improvements can be made without sacrificing privacy, presenting a practical and efficient approach to private set operations.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3141"},"PeriodicalIF":2.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DDoS attack detection in Edge-IIoT digital twin environment using deep learning approach. 基于深度学习方法的边缘工业物联网数字孪生环境中的DDoS攻击检测。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-29 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3052
Feras Al-Obeidat, Adnan Amin, Ahmed Shuhaiber, Inam Ul Haq
{"title":"DDoS attack detection in Edge-IIoT digital twin environment using deep learning approach.","authors":"Feras Al-Obeidat, Adnan Amin, Ahmed Shuhaiber, Inam Ul Haq","doi":"10.7717/peerj-cs.3052","DOIUrl":"10.7717/peerj-cs.3052","url":null,"abstract":"<p><p>The industrial Internet of Things (IIoT) and digital twins are redefining how digital models and physical systems interact. IIoT connects physical intelligence, and digital twins virtually represent their physical counterparts. With the rapid growth of Edge-IIoT, it is crucial to create security and privacy regulations to prevent vulnerabilities and threats (<i>i.e</i>., distributed denial of service (DDoS)). DDoS attacks use botnets to overload the target system with requests. In this study, we introduce a novel approach for detecting DDoS attacks in an Edge-IIoT digital twin-based generated dataset. The proposed approach is designed to retain already learned knowledge and easily adapt to new models in a continuous manner without retraining the deep learning model. The target dataset is publicly available and contains 157,600 samples. The proposed models M1, M2, and M3 obtained precision scores of 0.94, 0.93, and 0.93; recall scores of 0.91, 0.97, and 0.99; F1-scores of 0.93, 0.95, and 0.96; and accuracy scores of 0.93, 0.95, and 0.96, respectively. The results demonstrated that transferring previous model knowledge to the next model consistently outperformed baseline approaches.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3052"},"PeriodicalIF":2.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453828/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A defensive model and implementation baseline for the metaverse and extended reality systems. 元现实和扩展现实系统的防御模型和实现基线。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-29 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3054
Sara Qamar, Hasan Tahir, Zahid Anwar, Naveed Ahmed, Shahzaib Tahir, Muhammad Aleem
{"title":"A defensive model and implementation baseline for the metaverse and extended reality systems.","authors":"Sara Qamar, Hasan Tahir, Zahid Anwar, Naveed Ahmed, Shahzaib Tahir, Muhammad Aleem","doi":"10.7717/peerj-cs.3054","DOIUrl":"10.7717/peerj-cs.3054","url":null,"abstract":"<p><p>The metaverse and extended reality (XR) systems are vulnerable to emerging security threats, as developers have prioritized competitive business gains over security. The virtual entities, immersive experiences, and lack of centralized governance pose significant challenges in establishing standardized guidelines for XR systems and its stakeholders. In this research, a panoramic view is presented to identify mitigation strategies and defensive capabilities, including authenticity, privacy, integrity, interoperability, virtual forensics, and incident reporting to counter potential threats. To facilitate the implementation of a secure XR system, a novel baseline model is introduced, outlining key attributes and functions aligned with the available libraries. A statistical analysis is performed to assess the quality and effectiveness of development resources in embedding novel XR security features. Furthermore, this research assesses the security posture of prominent XR systems and examines the applicable regulatory frameworks in immersive environment. Finally, security recommendations are proposed to counter the threat landscape of XR and the metaverse.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3054"},"PeriodicalIF":2.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhancing reliable and energy-efficient UAV communications with RIS and deep reinforcement learning. 利用RIS和深度强化学习增强可靠和节能的无人机通信。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-29 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3031
Wasim Ahmad, Umar Islam, Abdulkadhem A Abdulkadhem, Babar Shah, Fernando Moreira, Ali Abbas
{"title":"Enhancing reliable and energy-efficient UAV communications with RIS and deep reinforcement learning.","authors":"Wasim Ahmad, Umar Islam, Abdulkadhem A Abdulkadhem, Babar Shah, Fernando Moreira, Ali Abbas","doi":"10.7717/peerj-cs.3031","DOIUrl":"10.7717/peerj-cs.3031","url":null,"abstract":"<p><p>The rapid growth in wireless communication demands has led to a surge in research on technologies capable of enhancing communication reliability, coverage, and energy efficiency. Among these, uncrewed aerial vehicles (UAV) and reconfigurable intelligent surfaces (RIS) have emerged as promising solutions. Prior research on using deep reinforcement learning (DRL) to integrate RIS with UAV concentrated on enhancing signal quality and coverage, but it ignored the challenges caused by electromagnetic interference (EMI). This article introduces a novel framework addressing the challenges posed by EMI from Gallium nitride (GaN) power amplifiers in RIS-assisted UAV communication systems. By integrating DRL with quadrature phase shift keying (QPSK) modulation, the proposed system dynamically optimizes UAV deployment and RIS configurations in real-time, mitigating EMI effects, improving signal-to-interference-plus-noise ratio (SINR), and enhancing energy efficiency. The framework demonstrates superior performance, with an SINR improvement of up to 6.5 dB in interference-prone environments, while achieving a 38% increase in energy efficiency compared to baseline models. Additionally, the system significantly reduces EMI impact, with a mitigation rate of over 70%, and extends coverage area by 35%. The integration of QPSK and DRL allows for real-time decision-making that balances communication quality and energy consumption. These results show the system's potential to outperform traditional methods, particularly in dynamic and challenging environments such as urban, disaster recovery, and remote settings.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3031"},"PeriodicalIF":2.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453847/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhanced information cross-attention fusion for drug-target binding affinity prediction. 增强信息交叉关注融合,预测药物靶点结合亲和力。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-28 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3117
Ailu Fei, Yihan Wang, Tiantian Ruan, Yekang Zhang, Min Yao, Li Wang
{"title":"Enhanced information cross-attention fusion for drug-target binding affinity prediction.","authors":"Ailu Fei, Yihan Wang, Tiantian Ruan, Yekang Zhang, Min Yao, Li Wang","doi":"10.7717/peerj-cs.3117","DOIUrl":"10.7717/peerj-cs.3117","url":null,"abstract":"<p><strong>Background: </strong>The rapid development of artificial intelligence has permeated many fields, with its application in drug discovery becoming increasingly mature. Machine learning, particularly deep learning, has significantly improved the efficiency of drug discovery. In the core task of predicting drug-target affinity (DTA), deep learning enhances predictive performance by automatically extracting complex features from compounds and proteins.</p><p><strong>Methods: </strong>Traditional approaches often rely heavily on sequence and two-dimensional structural information, overlooking critical three-dimensional and physicochemical properties. To address this, we propose a novel model-Cross Attention Fusion based on Information Enhancement for Drug-Target Affinity Prediction (CAFIE-DTA)-which incorporates protein 3D curvature and electrostatic potential information. The model approximates protein surface curvature using Delaunay triangulation, calculates total electrostatic potential <i>via</i> Adaptive Poisson-Boltzmann Solver (APBS) software, and employs cross multi-head attention to fuse physicochemical and sequence information of proteins. Simultaneously, it integrates graph-based and physicochemical features of compounds using the same attention mechanism. The resulting protein and compound vectors are concatenated for affinity prediction.</p><p><strong>Results: </strong>Cross-validation and comparative evaluations on the benchmark Davis and KIBA datasets demonstrate that CAFIE-DTA outperforms existing methods. On the Davis dataset, it achieved improvements of 0.003 in confidence interval (CI) and 0.022 in R<sup>2</sup>. On the KIBA dataset, it improved MSE by 0.008, CI by 0.005, and R<sup>2</sup> by 0.017. Compared to traditional models relying on 2D structures and sequence data, CAFIE-DTA shows superior performance in DTA prediction. The source code is available at: https://github.com/NTU-MedAI/CAFIE-DTA.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3117"},"PeriodicalIF":2.5,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453779/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Risk assessment based on a new decision-making approach with fermatean fuzzy sets. 基于fermatean模糊集的风险评估新决策方法。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-28 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.2990
Hilal Biderci, Ali F Guneri
{"title":"Risk assessment based on a new decision-making approach with fermatean fuzzy sets.","authors":"Hilal Biderci, Ali F Guneri","doi":"10.7717/peerj-cs.2990","DOIUrl":"10.7717/peerj-cs.2990","url":null,"abstract":"<p><strong>Background: </strong>This study presents a new approach to decision-making based on the selection of decision-makers according to evaluated criteria in multi-criteria decision-making (MCDM) methods. Therefore, sub-decision-maker groups (SDMGs) are created for each evaluated criterion. The SDMG approach, which is created according to the criteria, offers a more flexible and dynamic structure than the existing approaches. This approach aims to use the expertise and knowledge of decision-makers more effectively. The decision-making approach presented in this study offers an innovative model and adds a new dimension to decision-making processes. This decision-making approach is applied to the plastic injection moulding machine risk assessment, as it involves different criteria. In addition to classical risk parameters such as probability, severity, frequency, and detectability, new parameters such as human error, machine error, and existing safety measures are also used in the risk assessment.</p><p><strong>Methods: </strong>The integration of the analytic hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS) methods into the interval valued fermatean fuzzy set (IVFFS) environment makes an important contribution to a more comprehensive consideration of risks and uncertainties in the risk assessment process. The IVFF-AHP method is used to weight the risk parameters and determine the hazard scores, and the TOPSIS method is used to rank the hazards. A holistic and systematic approach to risk assessment has been achieved by integrating these two methods. Modelling of these methods is carried out using MATLAB_R2024a software.</p><p><strong>Results: </strong>According to the evaluated criteria, it was concluded that the determination of the decision makers separately is applicable to the decision-making process. Identifying the existing safety measures parameter as the most important risk parameter emphasizes the central role of this factor in risk assessment. In addition, machine error and human error parameters are also found to be important in risk assessment. These parameters, which are used for the first time in the literature, offer a broader perspective than traditional methods and provide significant advantages in risk assessment. According to the evaluations, electricity, asphyxiating and toxic gases, and hot water use are determined as the most risky hazards. The sensitivity and comparative analysis performed in the study confirm that the proposed methodology produces consistent and reasonable results.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e2990"},"PeriodicalIF":2.5,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453700/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comparing hand-based and controller-based interactions in virtual reality learning: effects on presence and interaction performance. 比较虚拟现实学习中基于手和基于控制器的交互:对在场和交互性能的影响。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-28 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3168
Murat Saran
{"title":"Comparing hand-based and controller-based interactions in virtual reality learning: effects on presence and interaction performance.","authors":"Murat Saran","doi":"10.7717/peerj-cs.3168","DOIUrl":"10.7717/peerj-cs.3168","url":null,"abstract":"<p><p>Virtual reality (VR) holds significant promise for enhancing science education by providing immersive and interactive learning experiences. However, the optimal interaction modality within educational VR environments remains an open question. This study investigates the impact of hand-based <i>vs</i>. controller-based interaction on sixth-grade students' sense of presence and interaction performance in a VR science laboratory simulation. Fifty-four sixth-grade students were randomly assigned to either a hand-based interaction group or a controller-based interaction group. Participants completed three interactive science experiments (solar system, electrical circuits, and force/energy) within a virtual laboratory environment designed to mimic their school's physical lab. Presence was assessed using a validated Turkish adaptation of the Presence Questionnaire (PQ), while interaction performance was evaluated using a structured observation form completed by a school teacher. Independent samples t-tests and Mann-Whitney U tests were used to compare the presence and performance scores between the groups. Supplementary analyses explored the effects of gender and prior VR experience. Contrary to expectations, no significant differences were found in either presence (t(49.4) = -0.01, <i>p</i> = 0.992) or interaction performance (t(52) = -1.30, <i>p</i> = 0.199) between the hand-based and controller-based interaction groups. Both interaction modalities yielded comparable levels of self-reported presence and observed performance. However, an unexpected finding emerged regarding performance. A supplementary analysis revealed a significant main effect of gender on performance scores (F(1, 50) = 4.844, <i>p</i> = 0.032), independent of interaction type. Specifically, males demonstrated significantly higher performance than females. This study suggests that, for sixth-grade students engaging in these specific VR science simulations, hand-based and controller-based interactions are equally effective in terms of fostering presence and supporting interaction performance. These findings have practical implications for the design and implementation of VR learning environments, particularly in resource-constrained settings where the reduced maintenance and hygiene concerns associated with hand-based interaction may be advantageous.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3168"},"PeriodicalIF":2.5,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453734/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Improving course evaluation processes in higher education institutions: a modular system approach. 改进高等院校课程评价过程:模块化系统方法。
IF 2.5 4区 计算机科学
PeerJ Computer Science Pub Date : 2025-08-28 eCollection Date: 2025-01-01 DOI: 10.7717/peerj-cs.3110
İlker Kocaoğlu, Erinç Karataş
{"title":"Improving course evaluation processes in higher education institutions: a modular system approach.","authors":"İlker Kocaoğlu, Erinç Karataş","doi":"10.7717/peerj-cs.3110","DOIUrl":"10.7717/peerj-cs.3110","url":null,"abstract":"<p><p>Course and instructor evaluations (CIE) are essential tools for assessing educational quality in higher education. However, traditional CIE systems often suffer from inconsistencies between structured responses and open-ended feedback, leading to unreliable insights and increased administrative workload. This study suggests a modular system to address these challenges, leveraging sentiment analysis and inconsistency detection to enhance the reliability and efficiency of CIE processes.</p><p><strong>Background: </strong>Improving the reliability of CIE data is crucial for informed decision-making in higher education. Existing methods fail to address discrepancies between numerical scores and textual feedback, resulting in misleading evaluations. This study proposes a system to identify and exclude inconsistent data, providing more reliable insights.</p><p><strong>Methods: </strong>Using the Design Science Research Methodology (DSRM), a system architecture was developed with five modules: data collection, preprocessing, sentiment analysis, inconsistency detection, and reporting. A dataset of 13,651 anonymized Turkish CIE records was used to train and evaluate machine learning algorithms, including support vector machines, naive Bayes, random forest, decision trees, K-nearest neighbors, and OpenAI's GPT-4 Turbo Preview model. Sentiment analysis results from open-ended responses were compared with structured responses to identify inconsistencies.</p><p><strong>Results: </strong>The GPT-4 Turbo Preview model outperformed traditional algorithms, achieving 85% accuracy, 88% precision, and 95% recall. Analysis of a prototype system applied to 431 CIEs identified a 37% inconsistency rate. By excluding inconsistent data, the system generated reliable reports with actionable insights for course and instructor performance. The purpose of this study is to design and evaluate a new system using the Design Science Research (DSR) approach to enhance the accuracy and reliability of course evaluation processes employed in higher education institutions. The modular system effectively addresses inconsistencies in CIE processes, offering a scalable and adaptable solution for higher education institutions. By integrating advanced machine learning techniques, the system enhances the accuracy and reliability of evaluation reports, supporting data-driven decision-making. Future work will focus on refining sentiment analysis for neutral comments and broadening the system's applicability to diverse educational contexts. This innovative approach represents a significant advancement in leveraging technology to improve educational quality.</p>","PeriodicalId":54224,"journal":{"name":"PeerJ Computer Science","volume":"11 ","pages":"e3110"},"PeriodicalIF":2.5,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12453702/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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