An Adaptive Biometric Authentication System for Online Learning Environments Across Multiple Devices

Score normalization applied to adaptive biometric systems

Higher education institutions have recently transitioned from face-to-face to online teaching and learning environments. However, academic staff lack sufficient training in applying emotional intelligence (EI) skills and strategies in online learning environments. Although literature addressing academics’ EI is sparse, some studies have suggested that lecturers’ EI greatly influences teaching and learning. This study used the concept of EI to understand students’ perceptions of how lecturers’ EI impacted their learning and engagement in an online learning environment. We conducted four online focus group interviews of 14 students pursuing a bachelor’s degree at two campuses of an Australian university, one in Melbourne and the other in Malaysia. Four main themes were identified using thematic analysis. Students discussed their perceptions and experiences on (a) vulnerabilities, coping and empathy; (b) relationships with lecturers, trust and safety; (c) communication, tone and voice; and (d) managing emotions of lecturers. Our findings suggest that lecturers’ EI impacted students’ learning and engagement in online learning spaces. However, the impact differs between Australia and Malaysia due to cultural differences. Drawing on the findings, we present online education good practices grounded in the theory of EI. Lecturers delivering online courses should consider employing these practices for effective teaching. Implications for practice or policy: Higher educational institutions need to support lecturers in developing the necessary EI skills to engage students in online learning. Lecturers need to make meaningful attempts to develop positive relationships with students in online forums to support students’ engagement. Lecturers working in online learning environments need to support students to develop friendships and connections with their peers. Lecturers need to include regular discussion breaks during online lectures to allow students to share their opinions and experiences.

The need for fool proof authentication procedures away from traditional authentication mechanisms like passwords, security PINS has led to the advent of biometric authentication in information systems. Biometric data extracted from physiological features of a person including but not limited to fingerprints, palm prints, face or retina for purpose of verification & identification is saved as biometric templates. The inception of biometrics in access control systems has not been without its own hitches & like other systems it has its fair share of challenges. Biometric fingerprints being the most mature of all biometric spheres are the most widely adopted biometric authentication systems. Biometric systems effectiveness lies on how secure they are at preventing inadvertent disclosure of biometric templates in an information system’s archive. This however has not been the case as biometric templates have been fraudulently accessed to gain unauthorized access in identification and verification systems. In order to achieve strong and secure biometric systems, biometric systems developers need to build biometric systems that properly secure biometric templates. Several biometric template protection schemes and approaches have been proposed and used to safeguard stored biometric templates. Despite there being various biometric template protection schemes and approaches in existence, none of them has provided the most authentic, reliable, efficient and deterrent means to totally secure biometric fingerprint templates. This research sought to establish status of the current biometric template protection techniques and methods by conducting a survey and analyzing data gathered from a sample of seventy-eight (78) respondents. We will report these results and give our conclusion based on findings of the survey in this paper.

Biometric person recognition poses a very challenging pattern recognition problem because of large variability in biometric sample qualityQuality encountered during testing and a restricted number of enrollment samples for training. Furthermore, biometric traits can change over time due to agingAgeing and change of lifestyle. Effectively, the noise factors encountered in testing cannot be represented by the limited training samplesTraining samples . A promising solution to training data deficiency and ageing is to use an adaptive biometric Adaptive biometrics system. These systems attempt to adapt themselves to follow the change in the input biometric data. Adaptive biometricsAdaptive biometrics deserves a treatment on its own right because standard machine-learning algorithms cannot readily handle changing signal quality. The aim of this chapter is to introduce the concept of adaptive biometric systems in terms of taxonomy, level of adaptation, open issues and challenges involved.

A biometric system is an amalgamation of algorithms that uses an individual’s unique biological data innate physical features (fingerprints, retina, face, ears, etc.) or behavioural features (signature, voice, keystroke dynamics, etc.) or both to authenticate the individual. This essentially makes a biometric system function as a pattern recognition system that helps an individual in any kind of adversarial environment. Hence, like any conventional authentication system, it is vulnerable to the attacks of malicious adversaries that try to manipulate the data and thus decline the security of the system by compromising its robustness. These possible attacks have not been considered while developing most biometric authentication systems. Our work describes multimodal biometrics, its feature extraction methods, research challenges and focuses on the major security issues in both unimodal and multimodal biometric systems. This paper summarizes some robust multimodal systems, their countermeasures and algorithms that have been devised to tackle these security challenges.KeywordsBiometricsMultimodal biometricsBiometric fusionSecurityAttacksCountermeasuresEncryption

The term adaptive biometric systems refers to biometric recognition systems in which an algorithm aimed to follow variations of the clients appearance has been implemented. Among others, the self update algorithm is used when only one biometric is available, and is able to add to the clients gallery novel data collected during system operation, on the basis of a updating threshold: if the novel data, compared with existing template(s), provide a matching score higher than the given threshold, they are added to the gallery. In order to avoid misclassification errors, thus inserting impostors into the clients gallery, this threshold is very conservative. Self-update algorithm has shown to be effective for many biometrics. However, no work tried to explain, so far, why self-update should work, in particular when a very conservative update threshold is used (zeroFAR threshold). This is the goal of the present paper, which provides a conceptual explanation of the self update mechanism coupled with a set of experiments on a publicly available data set explicitly designed for studying adaptive biometric systems.

In the past, instructional design of online learning has largely ignored culture in the creation of online learning environments. Because research in the interaction of culture and online learning is very sparse, an exploratory, blended study was conducted to assess whether there is evidence that one measurable aspect of learners’ culture interacts with the online learning environment in ways that can be observed and identified, and whether this interaction impacts learners’ motivation and behavior in those environments. “Culture” is a complex concept consisting of many interrelated behaviors and values. For this reason, the study focused on one single aspect of culture— Hofstede’s individualist/collectivist (IC) orientation—and investigated its relationship to learner behavior and motivation in online learning environments. This study found patterns of significant correlations between motivation and IC variables within the online learning environments, as well as between certain types of online interactions (particularly listserv usage) and IC variables. Patterns of correlations between IC scores and synchronous activities, asynchronous activities, individual components, and group work were clearly observable. Of these, the synchronous component seems to have the weakest associations, possibly due to a relatively small sample size. There is clearly an association between respondents’ emotional reactions to synchronous work and their IC scores; however, these coefficients are uniformly negative. This indicates that, as a learner collectivist score increases, the emotional reaction that the learner experiences as a result of synchronous components decreases. The results of this study indicate that further research in this area is warranted. Instructional designers and implementers should be aware of potential interactions between online learning environments and the cultural characteristics of the learners who utilize them. Understanding how a learner’s culture may interact with specific online learning components makes possible the exploration and creation of alternative means of supporting learners in the construction of knowledge.

The rapid growth of diverse learners in online learning has made it imperative for online instructors to incorporate multicultural resource curricula and instructional activities. This research aimed to explore online instructors' perceptions of culturally responsive pedagogy in online education; examine how instructors integrate culturally responsive pedagogy strategies in the online learning environment; and explore the challenges in facilitating cross‐cultural collaborative learning for students from different cultural backgrounds. Data were collected following a qualitative multi‐site case study method with five academic disciplines (Education, Social Sciences, Engineering, Physical Sciences and Health Sciences) in 12 colleges and universities in the United States of America. In all, 60 in‐depth and semi‐structured interviews with instructors (26 females and 34 males) were obtained and analysed following a constant comparative analysis approach. Results reflected that the instructors used cross‐cultural interactions to facilitate students' engagement and incorporated culturally responsive teaching. Besides, the findings revealed that most of the instructors integrated diverse and internationalized learning content to support diverse students and addressed the impact of multicultural education in online learning. It was, however, noted, that instructors in the physical science disciplines struggled to incorporate culturally diverse contents in their online classes. The findings of this study foster discourse on how best instructors could be aided to engage diverse students online more meaningfully. Practitioner notesWhat is already known about this topic Since studies of this nature are mostly undertaken in teaching and learning environments that are diverse in terms of student populations, both students and instructors are exposed to cultural differences in teaching and learning in multicultural/diverse online learning environments. Studies on multicultural/diverse online learning environments abound and have been undertaken for several years but the emphasis has mainly been to explore issues from the perspectives of students. Most online instructors assume that online learning provides equal opportunities to all students regardless of their cultural backgrounds and cultural differences; hence, instructors have mostly not been able to recognize cultural implications for students' learning to design inclusive instructional strategies to meet the learning needs of diverse students in online education. What this paper adds This study, unlike earlier ones with a similar focus, explored online instructors' perceptions of culturally responsive pedagogy (CRP), specifically with regards to the design, preparation and integration of multicultural learning contents and resources in online education. This study employed Scott et al.'s (2015) culturally responsive computing theory as a lens to connect students' prior learning experiences, knowledge, interests, strengths and weaknesses as a way to draw instructors' attention to how best diverse students can be aided to be innovative and succeed in the face of cross‐cultural challenges they face studying online. The study also contributes to the instructors' understanding of culturally responsive pedagogical principles in online spaces that recognize global identities and cultural experiences to meet the needs of diverse students in an online learning environment. Implications for practice and/or policy Instructors must develop online courses with the focus to bridge students' geographical and cultural backgrounds so that students will have the opportunity to share and connect with peers in online classrooms for effective collaboration and communication. Institutions that offer online education must make concerted efforts to provide continuous professional development opportunities for instructors of online courses on impacts of culture/diversity in the online classroom, and strategies for creating conducive online learning environments that value cultural differences, and social/educational experiences in ways that support students' learning. Institutions and stakeholders, through policy initiatives, should make frantic efforts to afford instructors with comprehensive knowledge and understanding of CRP in online learning to avoid the assumption that students in online courses share similar learning characteristics and bring to the online learning the same experiences and cultural backgrounds.

The Framework for DIRECTED Online Learning Environments

By investigating the current state of online learning environments in medical education and students' academic emotions, this study aims to further understand the association between online learning environments and academic emotions, thereby providing insights for optimizing the online learning environment in medical education. A cross-sectional study. The study employed a convenience sampling method to select participants from a sample of 317 medical school students at a university in China. The study was conducted from September to November 2023. Data was collected using General Information Questionnaire, Online Learning Environment Assessment Scale, and College Students' General Academic Emotions Questionnaire. Pearson's correlation coefficient was used to examine the association between the online learning environment and academic emotions. And the ENTER method was chosen for multiple linear regression analysis. The results showed that content design had a significant positive association on positive activating emotions. Learning assessment had significant negative association on negative activating emotions and negative deactivating emotions. Website design had a significant positive association on negative deactivating emotions. In order to increase positive academic emotions and decrease negative emotions among medical students in online learning, improvements can be made in the areas of content design, learning assessment, and website design, which in turn will improve the effectiveness of online learning.

Traditional online learning environments generally use a one-size-fits-all approach, neglecting individual learner needs, goals, and cognitive abilities. Adaptive Educational Hypermedia (AEH) systems emerged to address this by personalizing learning content based on user profiles. The Adaptive Learning System is a computerized system developed to enhance digital interactive educational content teaching and learning. The system’s Adaptive algorithm automatically detects learners’ strengths and weaknesses through the adaptation process and provides personalized learning materials, feedback, and guidance during their learning. Adaptive content allows learners to learn the material at their own pace while providing additional support, evaluation, and resources tailored to each learner. In traditional educational systems, every student is given access to the same learning content regardless of their individual learning needs. Higher education institutions face various challenges when testing and implementing adaptive learning systems for their domain of knowledge. Issues related to technical challenges include processing real-time data, difficulties consolidating learning concepts and solutions into existing learning management systems, and the complexity, ease of use, and usability of adaptive learning systems. However, despite the advancement and technical sophistication in adaptive algorithms, most AEH systems still face significant usability challenges. Learners often struggle with complex interfaces, limited system responsiveness, and poor adaptation to diverse demographics and subject backgrounds. Consequently, the current adaptive systems are underutilized in higher education, with limited empirical evidence on their effectiveness in enhancing student engagement, engagement, quality of experience (QoE), and academic performance. While foundational research work (Brusilovsky, 2001; De Bra et al., 2013) and recent studies (Liu & Lim, 2020; colMOOC project) have shown the importance of adaptive educational hypermedia, yet ongoing issues persist regarding usability, learner control (Paramythis & Loidl-Reisinger, 2004), and empirical validation across varied higher education settings (Latham et al., 2004; Educause, 2018). Systematic investigations into user-controllable personalization and its effects on inclusivity and academic achievement remain limited (Xie et al., 2019; Lundqvist; Warburton, 2019). Furthermore, Li et al. (2021) highlighted that existing systems lack comprehensive cognitive modelling and fail to adequately adapt to individual learner dispositions, which restricts their intelligence and adaptability. This complexity in adaptive systems continues to pose challenges for education overall, as emphasized by Fengying Li, Yifeng He, and Qingshui Xue (2021). Addressing these issues, Dubiel et al. (2022) propose a framework for adaptive user interfaces that integrates the interaction environment to enhance system responsiveness. Therefore, there remains a significant gap in the literature regarding the lack of empirical evaluation of user-controlled personalization, particularly in real-world, multi-disciplinary higher education contexts. Existing research has focused mainly on adaptive algorithmic and technical development, but has not given sufficient attention to practical usability (the lack of effective, usable AEH systems, learner diversity, and actual learner-centered outcomes). Moreover, there is a lack of comprehensive frameworks for evaluating the usability of adaptive educational hypermedia (AEH), and there is limited research on how these adaptive systems can foster inclusivity and fairness among diverse learner populations. Therefore, there is an urgent need to address the usability and complexity problems in AEH systems and to suggest the creation of usable, effective, personalised, learner-centric, and user-controllable AEH systems for higher education environments. This research study addresses these gaps by introducing a personalized, user-controllable Adaptive Educational Hypermedia (AEH) framework specially designed for a Higher Education setting. It evaluates multiple versions of adaptive learning systems across multiple disciplines (English, Malay, Computer Science) revealing significant enhancements in both student achievement and satisfaction. The study not only evaluates multiple versions of adaptive systems but also offers practical recommendations for software developers and educators seeking to implement effective, more intuitive, and learner-centric adaptive systems within real higher educational environments. By exploring the relationships between learner demographics, usability, and academic outcomes, the study promotes inclusivity and equity in digital education. More specifically, it introduces a novel user-controllable personalization feature that empowers learners to customize the learning content to improve their adaptive learning experience, addressing a major limitation found in existing systems. The findings demonstrate significant improvements in student performance and satisfaction with the system’s interface, thereby enhancing subject retention, confirming that adaptive learning systems can effectively improve the academic experience in higher education environments.

In-service teacher trainees experience with and preference for online learning environments during Covid-19 pandemic

This study is conducted to find out the correlation between students' knowledge sharing behaviors and learning community feeling in online learning environments. Correlational survey model was conducted in this study. The study group is consisted of 139 participants (46 male, 93 female) who are enrolled in distance and undergraduate and associate degrees in the Distance Education Centre of Amasya University in Turkey. The Distance Education Centre uses LMS software. In this study, 9-question Personal Information Form was used to get the demographic information of the participants. With the help of a personal information form, the participants were asked about their gender, class, department, which devices they used for LMS, their weekly stay in the LMS and the number of logins to the LMS. Also, the Sense of Community in Online Learning Scale used to collection data. A total of 139 participants were reached during the 5-week data collection process. The collected data were analysed with SPSS 25.0 program. As a result, participants' sense of community in online learning and knowledge sharing behavior were high. There was a moderately positive relationship between sense of community in online learning and knowledge sharing behavior in online learning. Also, students’ knowledge sharing behaviors and sense of community in online learning environment are affected by grade level, department, number of entry and online duration.

Teaching in blended and online learning environments requires different pedagogical approaches than teaching in face-to-face learning environments. How educators are prepared to teach potentially impacts the quality of instruction provided in blended and online learning courses. Teaching presence is essential to achieving student learning outcomes, yet previous research has focused on student perceptions of teaching presence. Therefore, the purpose of this mixed methods convergent parallel study was to explore educators’ preparation to teach, perceived teaching presence, and perceived teaching presence behaviors in blended and online learning environments. The study was designed to examine the differences in educators’ perceived teaching presence and preparation to teach in blended and online learning environments. An adapted Community of Inquiry Survey Instrument was used to measure faculty perceptions of teaching presence. Results indicated a statistically significant difference between perceived teaching presence of facilitation for faculty that completed certification courses in preparation to teach in blended and online learning environments, as compared to faculty that only received on-the-job training. Qualitative responses to corresponding interview questions supported the findings. The findings of this study provide information to university educators and administrators supporting the importance of faculty preparation specific to teaching in blended and online learning environments.

Many music educators are concerned about building healthy classroom communities as they prepare to transition to online or blended learning environments. Research involving distance education has indicated that several techniques in the design and delivery of online instruction can increase students’ sense of community, commitment to the course, and overall learning experience. The purpose of this research-to-resource article is to provide music educators with research-based strategies for establishing and connecting students to a sense of community in courses delivered partially or entirely online.