Personal Need Research Articles

GnRH agonist trigger in poor prognosis patients undergoing a multicycle approach through DuoStim or consecutive stimulations: a SWOT analysis.

Identify the most recent and significant evidence regarding the ovulation trigger within the framework of a multicycle approach through DuoStim, providing valuable insights for improving treatment strategies in patients with a poor prognosis. The trigger method plays a pivotal role in optimizing in-vitro fertilization (IVF) stimulation, influencing oocyte retrieval and maturation rates, as well as follicle recruitment in consecutive ovarian stimulations such as double stimulation. Decision-making involves multiple factors and, while guidelines exist for conventional stimulation, specific recommendations for the multicycle approach are not well established. The different methods for inducing oocyte maturation underscore the need for personalization of IVF protocols. The GnRH agonist trigger induces rapid luteolysis and establishes favorable hormonal conditions that do not adversely affect the recruitment of consecutive follicular waves in the context of DuoStim. It serves as a valid alternative to hCG in freeze-all cycles. This strategy might enhance the safety and flexibility of ovarian stimulations with no impact on oocyte competence and IVF efficacy.

An Investigation into the Causes of Tax Evasion and Avoidance by Small and Medium Enterprises (SMEs) and Their Effect on the Zambian Economy in Chililabombwe District

This study was purposed to investigate the causes of tax evasion and avoidance and its effect on the Zambian economy in Chililabombwe District of the Copperbelt Province. It had two-fold objectives: to examine the causes of tax evasion and avoidance in Chililabombwe District by SMEs, and to determine the effect of tax evasion and avoidance in Chililabombwe District on the Zambian economy. The study used a mixed method approach combining both qualitative and quantitative paradigms in which 110 sample size was targeted. One Hundred and ten (110) questionnaires were distributed and 79 were returned representing 72%. Purposive and convenient sampling techniques were used. Quantitative data was analysed through the SPSS version 16 while qualitative data was analysed through content analysis focusing on main unfolding themes from the interviews. The study discovered that that there are loopholes in the Zambia Revenue Authority's (ZRA) tax administration system which are due to inefficiencies or inadequate competence of tax collectors, which taxpayers exploit in evading and avoiding tax. The investigation also revealed that on account of the established loopholes, certain revenue collectors collude with taxpayers to commit tax fraud by accepting bribes from them while poor sales, high tax rates, and lack of tax education to SMEs were noted to be among key reasons for tax avoidance. Consequently, the study ascertained with concern that the levels of development in the district, in terms of social amenities, schools, road network, and youth / women empowerment programmes are very low. The study concluded that tax evasion and avoidance were real and rife among the SMEs on account of the factors cited and that mitigative policy measures were required without any further delays. Arising from the results of the study, it was strongly recommended that for tax evasion and avoidance to be mitigated, the revenue authority needs to urgently reform the tax system to make it equitable and fair coupled with rigorous tax education to the traders for sufficient tax knowledge and thereafter digitize tax remittances with ease for the traders to file returns without need for middle persons. Tax morale and ultimately revenue collection can be improved through tax education programs, integrity of tax collectors, and reduction of tax rates chargeable to SMEs. Enhanced training and sensitization to create awareness, reduce compliance cost, and simplify online technology for the overall positive impact on compliance among the SMEs are elements of paramount import for the success of the nation in meeting its socio-economic goals through guaranteed revenue collections by the Revenue House.

Personalized Reinforcement Learning with a Budget of Policies

Personalization in machine learning (ML) tailors models' decisions to the individual characteristics of users. While this approach has seen success in areas like recommender systems, its expansion into high-stakes fields such as healthcare and autonomous driving is hindered by the extensive regulatory approval processes involved. To address this challenge, we propose a novel framework termed represented Markov Decision Processes (r-MDPs) that is designed to balance the need for personalization with the regulatory constraints. In an r-MDP, we cater to a diverse user population, each with unique preferences, through interaction with a small set of representative policies. Our objective is twofold: efficiently match each user to an appropriate representative policy and simultaneously optimize these policies to maximize overall social welfare. We develop two deep reinforcement learning algorithms that efficiently solve r-MDPs. These algorithms draw inspiration from the principles of classic K-means clustering and are underpinned by robust theoretical foundations. Our empirical investigations, conducted across a variety of simulated environments, showcase the algorithms' ability to facilitate meaningful personalization even under constrained policy budgets. Furthermore, they demonstrate scalability, efficiently adapting to larger policy budgets.

Abstract 6709: P329G-Engager: A novel universal antibody-based adaptor platform for cancer immunotherapy

Abstract Bispecific immune cell engagers are showing promise in cancer immunotherapy. To achieve optimal efficacy, there is a growing need for patient personalization, tackling intra-tumor heterogeneity, and simplified combination therapies. Here, we present a novel modular anti-P329G adaptor platform aiming to address these issues, which is based on the recognition of the P329G mutation in the Fc portion of a targeting adaptor antibody. This P329G mutation can serve to recruit different anti-P329G effector cell engagers, including innate cell engagers, T cell engagers, costimulators or immunocytokines. Specifically, upon identifying patient-specific tumor surface targets, the primary antigen-binding IgG1 antibodies bearing Fc-silencing P329G LALA mutations are applied. Subsequently, based on the tumor’s immune profile, the best-suited anti-tumoral effector cell type is chosen for recruitment and activation. Based on this information, the secondary antibody recognizing the P329G mutation is chosen from an array of effector cell engagers with different modes of action: P329G-T cell bispecifics (P329G-TCB), ADCC-competent P329G innate cell engagers (P329G-ICE), P329G costimulatory molecules (P329G-CD28/4-1BBL) or P329G immunocytokines (P329G-IL2v). In vitro assays showed all P329G modalities inducing anti-tumoral and/or immunomodulatory cell activity. Anti-tumoral efficacy of secondary antibodies was observed only in presence of tumor-targeted P329G adaptors, while no effect was observed in their absence. The readouts consisted of tumor killing quantification, CD4+ and CD8+ T cell activation, cytokine release and cytokine receptor signaling. As a proof of concept study in vivo, an experiment in MKN-45 (CEACAM5+)-bearing humanized mice was performed, using an anti-CEACAM5 P329G-IgG adaptor and a P329G-TCB. Both tumor volume shrinkage and T cell infiltration into the tumor confirmed anti-tumoral efficacy of the platform, as compared to a conventional CEACAM5-targeted TCB. Neither the individual P329G IgG nor the individual P329G-TCB induced anti-tumoral efficacy, validating the requirement for primary and secondary antibody binding for T cell engaging activity. These results provide in vitro and in vivo evidence that the universal P329G engager platform can be used as an efficacious cancer treatment. Ultimately, this modular approach may enable off-the-shelf personalization via combination of patient-specific antibodies and universal effector cell engagers based on the patient’s tumor target and immune profile. Citation Format: Marlena Surowka, Idil Hutter-Karakoc, Diana Darowski, Christina Claus, Claudia Ferrara Koller, Anne Freimoser-Grundschober, Thomas Hofer, Andrzej Sobieniecki, Denis Assisi, Stephane Leclair, Ekkehard Moessner, Pablo Umaña, Maria Amann, Christian Klein. P329G-Engager: A novel universal antibody-based adaptor platform for cancer immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6709.

Behavioral Factors Influencing Investment Decision of Individual Investor at Nepalese Stock Market

The investment decision of individual investor is influenced by macro/micro economic and behavioral factors. Interest rate, economic growth, inflation, government policy, technological developments, etc., are the macro-economic factors, and firm size, book-to-market equity, cash flow yield, earnings yield, and dividend yield, etc. are the micro-economic factors whereas accounting information, advocate suggestion, personal financial needs, social relevance, self-image/firm-image coincidence, etc. are the behavioral factor. This paper has analyzed the perception of investor on the selected behavioral factors that makes influence on individual investor's investment decisions at Nepalese stock market. Using the structured survey questionnaire, this study concludes that behavioral factors have significant influence on investment decision of individual investor. This study revealed that to get rich quickly, reputation of the firm, feelings for a firm’s products and services, and firm status in industry are the major influencing Self–image/Firm-image factor. On the other hand, friend or coworker's recommendations, family member opinion, and broker recommendation are the most significant influencing Advocate Recommendation factors. Similarly, return maximizing, stock marketability, ease of obtaining borrowed funds, and expected dividends are the major Personal Financial Needs factors, and past trends of stock, information of dividend, price level of other stock, and information of the stock market are the major Market Information factors for influencing investment decision of individual investor at Nepalese stock market.

Exploring Interactions in the Co-Production of Social Care Services with Vulnerable Citizens

ABSTRACT ‘This study examines the interactions that occur among researchers, service providers and vulnerable citizens during the co-production of social care services, which is where value is co-created. An in-depth study of co-design and co-assessment workshops with vulnerable citizens revealed that co-production could be reached only at some points of the overall group discussion. Results highlight that vulnerable citizens need time to share and compare their personal experiences and need to be guided in the process by expert facilitators. This study also provides four innovative communicative strategies for supporting the facilitators in involving vulnerable citizens during the co-production of social care services.

The Impact of E-Service Quality on E-Satisfaction and Loyalty in Btn Mobile: in The Evidence of BTN Mobile Banking Users in Jabodetabek

This research study the relationship and the impact of e-Service Quality on e-Satisfaction and loyalty in the BTN Mobile Banking users. This study uses modified dimensions of the E-SERVQUAL instrument to determine the e-SQ of BTN Mobile Banking service in JABODETABEK which are Personal Needs, Site Organization, User-friendliness and Efficiency. 103 respondents were involved in this study and the results showed E-SQ have significant impact to E-Satisfaction and Loyalty. Data analysis was performed using SEM-PLS. The limitations of this study are that the scope of the population is only in the special province of Jakarta, and the variables related to e-satisfaction are only emphasized from the perspective of user experience and interface while the research scope on e-satisfaction is very wide. The findings of this study show that in Internet banking, in addition to the technical and functional aspects of -SQ reflects the importance of contribution to e-satisfaction and e-loyalty.

Empowering Progress and Unveiling the Impact of Satisfying Employee's Personal Needs in Saudi Arabia's Manufacturing Sector

This study aimed to analyze the impact of satisfying employee’s personal needs on the Company Performance in the Saudi Manufacturing Sector. In particular, the researcher intended to assess the practitioners to develop their strategy to enhance employee engagement. To do that, the researcher observed the relationship between satisfying employee’s personal needs on employees’ performance and how it contributes to the company growth. In this context, quantitative and qualitative analyses approaches were used to address the research objectives. The researcher used an explanatory sequential mixed research design which was constructed from web-based survey and semi-structured face-to-face interviews. Accordingly, 578 employees working in different organizations in Saudi Manufacturing Sector participated in the survey questionnaires. On the other hand, for the qualitative part, 30 employees working in panel boards manufacturing factory were purposely selected to participate in face-to-face interviews. Significant relationships were observed from the quantitative analysis then verified using qualitative analysis. The findings showed that employees can positively contribute in Company effectiveness when their personal needs are satisfied. Most of the participants believed that their performance is significantly impacted if the company participates in satisfying their personal needs and that positively impacts Company progress.

Beyond play: a comparative study of multi-sensory and traditional toys in child education

As educational paradigms evolve, the integration of multi-sensory theory into the design of children’s educational toys presents a promising avenue for enhancing learning experiences. This paper explores the efficacy of multi-sensory toys in improving children’s attraction, interest, and learning efficiency through a systematic review and a pilot empirical study. The study specifically assesses the hypothesis that multi-sensory educational toys significantly increase children’s engagement and learning outcomes compared to traditional toys. Conducted with a diverse group of children aged 3–6 in Guangzhou and Shenzhen, China, the research employs both quantitative and qualitative methodologies, including engagement metrics and observational studies. The findings suggest that multi-sensory toys not only hold the potential to augment learning experiences but also require careful consideration of individual learning styles and preferences. The paper concludes with a discussion on the implications for future research and toy design, emphasizing the need for continued innovation and personalization in the development of educational toys to cater to the multifaceted needs of young learners.

Democracies in Our Changing Times

The aim of the study is to examine how the transition from the orderly 20th century to the chaotic Post-modern 21st century, affects, reshapes the nature, character and the functionality of the Post-modern Democracy. This examination is conducted thru two phases that explore four areas of behavior; Personal—Needs and Feelings, Economic Drives, Social Concerns and Political Motivations. A short sum-up is presented on two comparison tables. Afterwards, a third section discusses some challenges for the future. Finally, some concluding practical points are offered for implementation. The first phase examines how people’s conduct and expectations, are changing during the transition period. It points-out that people change their aspirations and expectations, as they feel free and ready for meeting new challenges. However, at the same time, grows the number of confused individuals, who limp behind progress and need a special treatment. The economy at that time, has promoted Globalization and High-Tec industries. At the same time, society became heterogeneous and instable, while citizens, in general, seek stability and prosperity. In politics, new voters look for a greater influence and a deeper involvement in the work of government. In sum, many people want to feel, the genuine spirit of the promising post-modern era. The second phase examines the effects and impacts of the transition on the nature and functionality of the Democratic state. It explores the similar four areas and conclude that the study’s observations, well indicate how people’s demands and behavior had changed and expanded due to the requirement to fit better and comply faster, with the Post-modern Chaotic Views. Further, some improving steps for empowering Democratic states, are proposed. At the end, some short practical points are offered for assisting professional, who eventually carry-out most of the implementation work. In sum, the 21st century foresees promising and inspiring prospects for Democratic states. The implementation of these forecasts depends mainly on a solid and consistent determination of the citizens and their leaders.Most Democracies need to run a continual decisive civic order for assuring and securing their people “Blessing of Liberty”. Only history will tell whether and when this inspiring dream would come through.

Ageing with Parkinson's: Identification of Personal Needs in the Northern Spanish Context.

As individuals diagnosed with Parkinson's disease enter older age, the myriad challenges and complications associated with this condition tend to escalate. Hence, there is a critical necessity to comprehensively discern the perceived needs of these individuals, along with their proposed remedies and essential support requisites. Additionally, understanding the perspectives of their families becomes imperative to formulate tailored interventions aimed at enhancing their overall development, progression, and quality of life. The study's main objective is to assess the perceived needs of individuals with PD and their family members, propose necessary solutions, and suggest future perspectives. The study encompassed a cohort of 268 participants, comprising 179 individuals diagnosed with Parkinson's disease and 89 of their relatives. A meticulously designed structured interview instrument consisting of 93 items was employed to assess various domains encompassing perceived needs, institutional support mechanisms, essential solutions, and future anticipations. Results: Statistically significant differences were found in health resources, social services resources, obstacles, solutions, and future outlook, with higher mean values from the relatives. Conclusions: The results highlight the most concerning needs in this context. Specifically, those needs related to health resources, social services resources, and future outlook present the greatest differences between the two subsamples, with the family members perceiving more needs. This alignment extended to both the categorization of unmet needs and the requisite solutions envisioned to address them. Suggested improvements include a sociosanitary strategy, stakeholder involvement, and prioritizing flexible home assistance to support older individuals with PD and their families.

Peculiarities of motivation in sports training

The article examines the current issues of motivation in sports training and identifies its main features. It is noted that the study of motivation in sports training is important both from the point of view of science and practice, because during sports much attention is paid to the personality of the athlete, his professionally important qualities and individual typological features. It is determined that motivation is a process in which a person motivates himself to action, as a result of which he will achieve the goal and fulfill the tasks. It is emphasized that motivation in sports training is associated with intrinsic motivation and achievement motivation. Intrinsic motivation is what motivates a person to act to increase their self-confidence and independence, rather than for an external goal. Achievement motivation is a type of activity motivation that is associated with a person's need to succeed and avoid failure The main features of motivation in sports training are substantiated, namely: motivation in sports training has the form of a three-level pyramid, the higher the level, the higher the athlete's motivation to train; the second feature is the athlete's personal motives that encourage him or her to train systematically; the third feature is achievement motivation, which is a relatively stable attribute of the individual. However, it is also a dynamic formation and begins to act (actualizes) in interaction with situational factors, such as the value and probability (chances) of achieving success in a particular field of activity. Achievement motivation, i.e., the desire to succeed in a particular type of activity, includes not only achievement motives (stable personality attributes), but also situational factors (value, probability of success, complexity of the task). Prospect for further research is to conduct an empirical study to determine the personal constructs of motivation in sports training.

How do reward personalization options influence the public’s willingness to participate in innovation projects? Insights from crowdfunding in Industry 5.0

PurposeThis study aims to examine the influence of reward personalization on financing outcomes in the Industry 5.0 era, where reward-based crowdfunding meets the personalized needs of individuals.Design/methodology/approachThe study utilizes a corpus of 218,822 crowdfunding projects and 1,276,786 reward options on Kickstarter to investigate the effect of reward personalization on investors’ willingness to participate in crowdfunding. The research draws on expectancy theory and employs quantitative and qualitative approaches to measure reward personalization. Quantitatively, the number of reward options is calculated by frequency; whereas text-mining techniques are implemented qualitatively to extract novelty, which serves as a proxy for innovation.FindingsFindings indicate that reward personalization has an inverted U-shaped effect on investors’ willingness to participate, with investors in life-related projects having a stronger need for reward personalization than those interested in art-related projects. The pledge goal and reward text readability have an inverted U-shaped moderating effect on reward personalization from the perspective of reward expectations and reward instrumentality.Originality/valueThis study refines the application of expectancy theory to online financing, providing theoretical insight and practical guidance for crowdfunding platforms and financiers seeking to promote sustainable development through personalized innovation.

Personalization of Affective Models Using Classical Machine Learning: A Feasibility Study

Emotion recognition, a rapidly evolving domain in digital health, has witnessed significant transformations with the advent of personalized approaches and advanced machine learning (ML) techniques. These advancements have shifted the focus from traditional, generalized models to more individual-centric methodologies, underscoring the importance of understanding and catering to the unique emotional expressions of individuals. Our study delves into the concept of model personalization in emotion recognition, moving away from the one-size-fits-all approach. We conducted a series of experiments using the Emognition dataset, comprising physiological and video data of human subjects expressing various emotions, to investigate this personalized approach to affective computing. For the 10 individuals in the dataset with a sufficient representation of at least two ground truth emotion labels, we trained a personalized version of three classical ML models (k-nearest neighbors, random forests, and a dense neural network) on a set of 51 features extracted from each video frame. We ensured that all the frames used to train the models occurred earlier in the video than the frames used to test the model. We measured the importance of each facial feature for all the personalized models and observed differing ranked lists of the top features across the subjects, highlighting the need for model personalization. We then compared the personalized models against a generalized model trained using data from all 10 subjects. The mean F1 scores for the personalized models, specifically for the k-nearest neighbors, random forest, and dense neural network, were 90.48%, 92.66%, and 86.40%, respectively. In contrast, the mean F1 scores for the generic models, using the same ML techniques, were 88.55%, 91.78% and 80.42%, respectively, when trained on data from various human subjects and evaluated using the same test set. The personalized models outperformed the generalized models for 7 out of the 10 subjects. The PCA analyses on the remaining three subjects revealed relatively little facial configuration differences across the emotion labels within each subject, suggesting that personalized ML will fail when the variation among data points within a subject’s data is too low. This preliminary feasibility study demonstrates the potential as well as the ongoing challenges with implementing personalized models which predict highly subjective outcomes like emotion.

Community Nurses' Perspectives on Conceptual Challenges Related to the Need for Nursing Care in Germany: A Constructivist Grounded Theory Study.

In Germany, a person's need for nursing care is assessed by evaluators according to the federal legal definition of the statutory long-term care insurance (LTCI). This definition and the associated standardized assessment tool constitute the conditions for providing nursing care in a community care setting in Germany. Furthermore, the community care setting is regulated by state law and negotiations between long-term care funds and associations of providers of nursing care. During nursing care, nurses engage in a variety of interactions with people. The extent to which the legal definition of the need for nursing care leads to challenges in these interactions is unclear. To address this knowledge gap, we conducted 22 problem-centered interviews with nurses in the community and analyzed the data using the constructivist grounded theory. The results revealed that the negotiation processes are settled within professional-family relationships and vary between the constructs of closeness and distance, advocacy and submission of responsibility, and ethos and technocracy; these are the central challenges nurses encounter in this setting. We discuss the implications and questions that arise from the findings for the nursing profession regarding its own current and future role as well as the design of nursing support in the community, to nurture more advanced nurse practitioners and community health nurses.

Math Gamification and ICT for University Learning: Systematic Review Article

The integration of math gamification and Information and Communication Technologies (ICT) in learning has been a subject of growing interest. This approach seeks to improve student motivation and performance by transforming mathematics teaching into a more interactive and hands-on experience in university education. In this research the PRISMA method was used, 80,000 academic papers were systematically reviewed on ICT-supported math gamification in education whereof 79,994 academic papers corresponding to other fields were excluded, selecting and using at the end 55 articles to conduct this research. Studies were identified that explored the effectiveness of this combination at different educational levels, with a particular emphasis on higher education. The results highlight a significant increase in student engagement and motivation, as well as improvement in knowledge retention as shown in the figures and tables of this research. Instant ICT feedback and the application of digital educational games contributed to have a more active learning adapted to individual needs. Although the results are encouraging, challenges remain, such as the need for personalization and equity in ICT access. Continued research seeks to perfect these strategies maximizing the benefits of gamification and ICT, highlighting the importance of adapting to the diversity of learning styles in mathematics education.

Can the prosocial benefits of episodic simulation transfer to different people and situational contexts?

Previous research has found that episodic simulation of events of helping others can effectively enhance intentions to help the same person involved and the identical situational context as the imagined scenarios. This ‘prosocial simulation effect’ is argued to reflect, at least in part, associative memory mechanisms whereby the simulation is reactivated when in the same situation as that imagined. However, to date, no study has examined systematically whether this ‘prosocial simulation effect’ can be transferred to response scenarios involving different people and/or situational contexts to the imagined scenarios, and if so, whether the degree of overlap with the imagined helping episode modulated the transfer effect. Across two experiments, we systematically varied the overlap of the simulated and response scenarios, both in terms of the persons in need and/or the situational contexts, and whether would influence the magnitude of prosocial simulation effect. Results from both experiments showed that the prosocial simulation effect can be transferred to response scenarios involving different people and situational contexts to the simulated scenarios. However, this finding was primarily driven by response scenarios that had a high degree of overlap to the simulated scenarios. The application of our findings to the practical implementation of simulation to promote prosociality in the real world is discussed.

Exploring return to work for patients with head and neck cancer.

The number of survivors of head and neck cancer (HNC) has steadily increased due to major advances in cancer care. However, cancer survivors who experience job loss face different challenges regarding return to work (RTW). Relatively few studies have integrated the experience encountered by patients. This mixed-methods study aimed to explore the experience and challenges of RTW in patients with HNC. Data were collected with structured questionnaires (n = 120) and semi-structured face-to-face interviews (n = 12). Relationships were found between patient's physical status, perceived stress, and social support. Patients who continued work, or not, had significant differences in reported physical function and stress. Four themes emerged from the qualitative data, including the perceived meaning of work, challenges for RTW, preparing for RTW, and social support. After diagnosis and treatment, patients perceived the meaning of work, such as personal value, responsibility, and financial need. They faced many challenges to RTW, including declining physical strength, workload, schedule rearrangement, speech difficulty, and changed appearance. In order to RTW, they prepared extensively and needed support from family and friends. This study revealed the experiences and challenges of RTW patients with HNC. The results allowed us to identify patients' concerns and ways that healthcare providers could improve the RTW process. Future studies may develop tailored approaches for RTW in healthcare and government policies.

Factors Influencing Interest In Entrepreneurship Among Bengkulu University Students Using The Theory Of Planned Behavior

This study involved seventh-semester students of Bengkulu University who are interested in entrepreneurship or already have a business and have taken entrepreneurship courses. The purpose of this study was to identify all the factors that influence students' entrepreneurial interests. Using Google Forms, an online questionnaire of fifty participants was used to collect data. The results of the research conducted using the theory of planned behavior show that the variables of self-efficacy, subjective norms, and need for achievement have a positive and significant influence on the entrepreneurial interest of Bengkulu University students. In other words, the stronger a person's self-efficacy, subjective norms, and need for achievement, the more interested in entrepreneurship they are.

An evolving learning style detection approach for online education using bipartite graph embedding

The increasingly widespread online education recently enabled a new form of teaching, learning, and overall educational outcome. However, the need of personalization is required as learners learn differently and learning follows a one-size-fits-all approach. Learning style is the most used personalization that plays an important role in learning. This learning style is a changeable trait that is influenced by the learner's behavior based on past experiences. As a result, knowing it over time helps to point learners in the right direction, motivate them, and enhance their learning outcomes. Research done so far does not take into account the changes in the behavior of learners, and the behavioral data is at large volume, making the existing approaches fail to capture and extract the behavior of learners efficiently. Inspired by these constraints, we propose an incremental learning style detection approach for online education with a bipartite graph embedding technique. We first construct a dynamic bipartite graph to represent the incremental interaction between learners and learning resources while learning. Then, introduce a dynamic bipartite graph embedding to learn the low dimensional representation of the constructed graph from the current and previous time. Finally, the low dimensional features are mapped to the selected Felder-Silverman learning style model (FSLSM) dimension each time to identify and group similar learners using the k-means clustering algorithm. The proposed approach can be integrated into different educational systems. Extensive experiments conducted using three datasets from 2015 KDD Cup courses demonstrate the effectiveness of our approach. Average of 93.19%, 95.76%, and 98.48% are achieved across the three datasets in accuracy compared to the existing approaches.