Effective Learning Research Articles

Methods and Strategies for Effective Teaching of Mathematics in Secondary Schools in Nigeria

If the mathematics is to be interesting rather than a dull experience for the students, the first steps must be to make it a positive rather than negative emotional experience for the teachers. The importance placed on the subject is derived from the fact that it would help the nation meet its quest for science and technological advancement. A lot required from the mathematics teacher in terms of methods and strategies for effective teaching and learning of mathematics in secondary schools to meet the learning expectation of the students and other stake-holders. You need satisfied, competent and confident teacher to produce satisfied and confident students. The teacher is a major learning resource in mathematics at any level. If he is effective, he is catalyst, a stimulator, an inspirer and facilitator. He has to be able to facilitate learning by creating opportunities which enable learner to investigate situations. He has to have internalized techniques which enable him to go beyond ordinary routine questions ending at the knowledge level, comprehension, application, analysis, synthesis and evaluation which may together be called higher intellectual skills and abilities have to be viewed by the mathematics teacher as important attributes to be acquired by his students. Teaching process cannot be said to be complete if assessment of the students, teachers and the, methods and strategies employed are not thoroughly carried out, The teacher must know the best techniques and methods of presenting his ideas to the students putting into consideration students interest, needs, individual differences, difficulties and abilities. Thus, for effective teaching and learning of mathematics, a teacher must embrace active learning as against the traditional method of teaching mathematics.

Mr. Tumbles’ Maya and the Multiplicity of Personas: Leveraging Illusion and Reality in Educational Game Design for SEN Language Learners

Educational research for Special Educational Needs (SEN) students has increasingly recognised the necessity for tailored approaches that accommodate diverse learning needs. Despite advancements, there remains a significant gap in the development of digital interventions, particularly video games, that cater to the language acquisition and communicative needs of SEN learners. This study explores how psychological paradigms from the popular children's television show ‘Mr. Tumble’ (made specifically for children with special educational needs) can inform the creation of language learning video games. By analysing the use of ‘Makaton’ a multimodal communication tool that combines signs, symbols, and speech the study highlights the potential of integrating similar techniques into game design to enhance accessibility and engagement for SEN learners. The philosophical understanding of Maya, which emphasises the illusory nature of multiplicity, serves as a theoretical framework to understand how a single character can embody multiple roles within a game, providing a consistent yet diverse learning experience. This approach not only aids in language comprehension but also fosters emotional and social development through relatable Non-Player Characters (NPCs) designed to interact meaningfully with learners. The study posits that incorporating these elements can create immersive, emotionally resonant educational experiences and the development of parasocial relationship between the learner and the digital intervention, that better meet the needs of SEN students, ultimately leading to more inclusive and effective language learning environments. Children simultaneously navigate multiple roles and perspectives, each reflecting a different aspect of reality in make-believe play. The critical importance of integrating this cognitive theoretical framework similar to that into the design of NPCs in educational video games is highlighted in this research. The paper argues that the paradigms of ‘multiplicity of mirrors’, when effectively incorporated into NPC design, can reflect different aspects of language, culture, and social interaction, offering learners a more immersive and multifaceted learning experience.

A systematic literature review of playful learning in primary education: teachers’ pedagogical activities

ABSTRACT The study conducts a Systematic Literature Review of empirical research spanning from 2014 to 2023, examining teachers’ pedagogical activities and their role in playful learning within primary education, with a focus on the use of pedagogical methods. Twenty-one relevant papers were selected using a four-phase PRISMA framework. The analysis reveals four distinct phases of pedagogical activities: planning, orientation, playing, and elaboration. Teachers play an important role, being responsible for planning activities, facilitating and supervising students’ learning, sparking their intellectual curiosity, and assessing their progress. Furthermore, the study highlights that the teacher can also become a co-player. The findings are discussed, contributing greatly to the understanding of playful learning processes in primary education and helping teachers develop effective playful learning pedagogical activities, thereby fostering a playful learning environment.

Nursing Students' Experiences and Perceived Learning Effectiveness of Patient Safety and Its Influencing Factors: An Integrative Literature Review.

To examine and synthesise the current literature to gain insights into nursing students' experiences, their perceived learning effectiveness of patient safety and its influencing factors. Integrative review. CINAHL, Medline, Scopus, and Embase databases from January 2011 to October 2023. Of the 5940 papers initially retrieved, 33 were included after title, abstract, and full-text screening. No papers were omitted through quality appraisal. Despite nursing students' generally positive attitude towards patient safety, their idealistic view did not translate into actual actions of upholding patient safety due to various factors. Moreover, their experiences and perceived effectiveness of learning patient safety were influenced by factors such as organisational safety culture and pedagogical contexts. Thematic analysis revealed four themes: 'perception, attitudes, and evaluation towards patient safety'; 'supportive organizational culture as impetus to promote patient safety'; 'perceived confidence, knowledge, and competence toward patient safety'; and 'educational contexts and pedagogies to promote learning of patient safety'. There is an inadequate focus on patient safety in clinical education compared to classroom education. Given that the clinical setting serves as an authentic learning environment of patient safety, nursing faculties play a crucial role in reforming existing nursing curricula to integrate patient safety education in both settings to ensure continuity of learning. Clinical nursing leaders should also proactively review and reform organisational culture and practices to enable nursing students' acquisition and internalisation of patient safety learning. This review highlighted the need for further collaboration between nursing faculties and healthcare institutions to advocate an environment conducive to nursing students' effective learning of patient safety. Reporting adheres to the Reporting items for systematic review and meta-analyses (PRISMA) 2020 guidelines. No patient or public contribution.

Boosting Algorithms for the Accident Severity Classification

<div><i>Background:</i> Road accident severity estimation is a critical aspect of road safety analysis and traffic management. Accurate severity estimation contributes to the formulation of effective road safety policies. Knowledge of the potential consequences of certain behaviors or conditions can contribute to safer driving practices. Identifying patterns of high-severity accidents allows for targeted improvements in terms of overall road safety. <i>Objective:</i> This study focuses on analyzing road accidents by utilizing real data, i.e., US road accidents open database called “CRSS.” It employs advanced machine learning models such as boosting algorithms such as LGBM, XGBoost, and CatBoost to predict accident severity classification based on various parameters. The study also aims to contribute to road safety by providing predictive insights for stakeholders, functional safety engineering community, and policymakers using KABCO classification systems. The article includes sections covering theoretical methodology, data analysis, model development, evaluation, performance metrics, and implications for improving road safety measures by comparing the performance of different boosting algorithms on the CRSS dataset. This study aims to identify the most effective machine learning algorithm to integrate into our product line in the near future, enabling accurate prediction of both accident severity and occurrence. <i>Results and Conclusions:</i> This study addresses challenges in evaluating performance metrics for different severity classes within unbalanced datasets, emphasizing the impact of dominant classes like Class O (O = no apparent injury) on overall accuracy. The investigation reveals the limitations and conservatism associated with imbalanced data in boosting models, hinting at a potential ceiling in their performance around 80%. Comparative analysis of algorithms, including CatBoost, XGBoost, and LGBM, demonstrates comparable performance even in the case of applying KNN algorithm for pre-processing, based on various metrics, especially accuracy, <i>F</i><sub>1</sub>-score, ROC-AUC, and PR-AUC for all severity classes. XGBoost with KNN algorithm did not show any significant performance improvement compared to the XGBoost without KNN algorithm. The study includes performance metrics, such as <i>F</i><sub>1</sub>-score, CM upper triangle, ROC-AUC, and PR-AUC applied to an accident analysis case study. Future work directions involve extending the application of CatBoost, XGBoost, and other algorithms to diverse datasets, exploring the capabilities of deep neural networks, refining dataset preparation for accuracy improvement, and creating unified tools for hazard analysis and risk assessment.</div>

Examining the Nexus between School Infrastructure and Instructional Materials on Academic Performance of Secondary School Students in Gombe State

The main purpose of the study was to examine the nexus between school infrastructure and instructional materials on the academic performance of secondary schools in Gombe State. The study was guided by two specific objectives, two research questions, as well as two null hypotheses. The research which was conducted in the Gombe State adopted a correlation research design. The population of the study was 24,216 subjects comprising 3,178 teachers and 21,038 Senior Secondary (SS II) students in public Secondary Schools in Gombe State. A multi-stage sampling procedure was adopted for the study in which simple random and purposive sampling were used. To determine the sample size, the Taro Yamane formula was used and a sample size of 348 was determined. Impact of School Facilities on Academic Performance Questionnaire” (ISFAPQ) was used as the instrument for data collection. The ISFAPQ was subjected to face validation by three experts and a trial test was conducted in Bauchi State which a reliability index of 0.89 was obtained using Cronbach Alpha. Data were collected through a questionnaire, and End of third-term results form. The data collected was analyzed using mean and standard deviation as well as linear regression analysis. The findings of the study revealed that school buildings and instructional materials had a significant impact on the academic performance of secondary school students in Gombe State. Based on the findings of the study, the following recommendations were made; The Government should ensure that school buildings are well-built and painted to facilitate teaching and learning. Instructional materials should be made available by the government and management of secondary schools to enable effective teaching and learning.

‘It’s like being there, but not in the way'. Exploring the use of virtual reality tools to stimulate reflection in Norwegian physical education teacher education

ABSTRACT The ongoing discussion surrounding the incorporation of technology in education has persisted over time. While technology offers significant advantages, such as improved collaboration and access to quality educational materials, it also introduces complexities such as the digital divide and concerns about data privacy, awareness and appropriate use. VR presents opportunities for future teachers to practice decision-making skills in controlled environments, although its effectiveness varies depending on the context and user perceptions. Research indicates that 360° videos enhance reflexivity, support practice and improve observation skills and content knowledge. However, the impact of viewing these videos individually versus in groups remains inconclusive. This study aims to explore students’ perspectives on the use of primary school physical education (PE) 360° video recordings and VR technology to enhance reflexivity. To this end, the theory of practice architectures was reviewed to provide a framework for analysing how educational practices interact with wider contexts, while another theory, reflection, helps to examine students’ critical thinking and introspection. The study intervention involved fourth-year students at a Norwegian university, who observed 360° recordings of physical education lessons using VR technology. Data were generated through these observations, which included the 360° recordings and small group interviews, and were analysed using reflective thematic analysis. The results highlight the importance of group dynamics, and that the authenticity of VR experiences can foster motivation and reflection. These insights can inform the design of future educational approaches in physical education teacher education (PETE), emphasising the need for careful consideration of technological and pedagogical practices to support effective and innovative teaching and learning to enhance experience and teaching.

Supplemental Material for The Paradox of Explaining: When Feeling Unknowledgeable Prevents Learners From Engaging in Effective Learning Strategies

Supplemental Material for The Paradox of Explaining: When Feeling Unknowledgeable Prevents Learners From Engaging in Effective Learning Strategies

A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

Clustering is a fundamental machine learning task which aims at assigning instances into groups so that similar samples belong to the same cluster while dissimilar samples belong to different clusters. Shallow clustering methods usually assume that data are collected and expressed as feature vectors within which clustering is performed. However, clustering high-dimensional data, such as images, texts, videos, and graphs, poses significant challenges for clustering tasks, such as indiscriminate representation and intricate relationships among instances. Over the past decades, deep learning has achieved remarkable success in effective representation learning and modeling complex relationships. Motivated by these advancements, Deep Clustering seeks to improve clustering outcomes through deep learning techniques, garnering considerable interest from both academia and industry. Despite many contributions to this vibrant area of research, the lack of systematic analysis and a comprehensive taxonomy has hindered progress in this field. In this survey, we first explore how deep learning can be integrated into deep clustering and identify two fundamental components: the representation learning module and the clustering module. Then we summarize and analyze the representative design of these two modules. Furthermore, we introduce a novel taxonomy of deep clustering based on how these two modules interact, specifically through multistage, generative, iterative, and simultaneous approaches. In addition, we present well-known benchmark datasets, evaluation metrics, and open-source tools to clearly demonstrate different experimental approaches. Finally, we examine the practical applications of deep clustering and propose challenging areas for future research.

Cyber-Securing Medical Devices Using Machine Learning: A Case Study of Pacemaker

This study aims to enhance the cybersecurity framework of pacemaker devices by identifying vulnerabilities and recommending effective strategies. The objectives are to pinpoint cybersecurity weaknesses, utilize machine learning to predict security breaches, and propose countermeasures based on analytical trends. The literature review highlights the transformation of pacemaker technology from basic, fixed-rate devices to sophisticated systems with wireless capabilities, which, while improving patient care, also introduce significant cybersecurity risks. These risks include unauthorized entry, data breaches, and life-threatening device malfunctions. The methodology in this study utilizes a quantitative research approach using the WUSTL-EHMS-2020 dataset, which includes network traffic features, patients' biometric features, and attack label. The step-by-step method of machine learning prediction includes data collection, data preprocessing, feature engineering, and models’ training using Support Vector Machines (SVM) and Gradient Boosting Machines (GBM). The implementation results used evaluation metrics like accuracy, precision, recall, and F1 score to show that GBM model outperformed the SVM model. The GBM model achieved higher accuracy of 95.1% compared to 92.5% for SVM, greater precision of 99.6% compared to 96.7% for SVM, better recall of 94.9% compared to 42.7% for SVM, and a higher F1 score of 76.3% compared to 59.0% for SVM, making GBM model more effective in predicting cybersecurity threats. This study concludes that GBM is an effective machine learning model for enhancing pacemaker cybersecurity by analyzing network traffic and biometric data patterns. Future recommendations for improving the pacemaker cybersecurity include implementing GBM model for threat predictions, integration with existing security measures, and regular model updates and retraining.

COVID-19 online learning challenges: Kazakhstan secondary schools case study

BackgroundThe COVID-19 pandemic necessitated a rapid transition to online learning (OL) globally, posing significant challenges for educational systems. This study investigates the experiences of secondary school students in Kazakhstan, highlighting the adaptation processes, educational outcomes, and challenges faced during this shift.MethodsData were collected through an online survey administered to 3,670 secondary school students across Kazakhstan, selected through convenience sampling. The survey comprised 21 questions using a combination of Likert-type scales and multiple-choice questions to capture students’ demographic details, satisfaction levels, perceived difficulties, and academic performance changes during OL. Data validation was ensured by cross-referencing responses, descriptive statistics, T-tests, ANOVA, correlation analysis, and regression were employed to analyze the data and identify factors influencing students’ attitudes toward OL and the associated challenges.ResultsThe results revealed that satisfaction with OL was positively correlated with satisfaction with education in general and negatively correlated with the level of difficulty in OL (p < 0.001). Rural students, while more satisfied with learning overall (p < 0.001), were less satisfied with OL compared to their urban peers, and also reported greater challenges (p < 0.05). A significant portion of respondents (44.2%) disagreed that OL was an effective learning method, and 43.7% expressed a need for face-to-face interaction with teachers, especially female and rural students (p < 0.001). Most students (40.8%) reported worse learning outcomes with OL, particularly urban students (p < 0.001), and 32.0% noted a decrease in motivation. Regression analysis identified older students and those who experienced greater difficulty with OL as less likely to prefer it, while those who showed improvement in academic performance and motivation were more favorable toward OL. These findings highlight the complexity of educational preferences and the disparities between urban and rural students during the pandemic.ConclusionWhile the findings may be applicable to other countries with similar educational systems, cultural, economic, and technological differences should be considered when generalizing the results. The insights gained from this study will be valuable for policymakers, educators, and academic institutions to improve the resilience and effectiveness of educational practices in the face of such challenges.

Music Generation Using Dual Interactive Wasserstein Fourier Acquisitive Generative Adversarial Network

Music composition, an intricate blend of human creativity and emotion, presents substantial challenges when generating melodies from lyrics which hinders effective learning in neural networks and the inadequate depiction of harmonic structure that fails to encapsulate the complex relationships between lyrics and melodies. The existing methods often struggle to balance emotional depth and structural coherence, leading to compositions that lack both the intended emotional resonance and musical consistency. To overcome these issues, this research introduces a novel approach named Dual Interactive Wasserstein Fourier Acquisitive Generative Adversarial Network (DIWFA-GAN), which integrates innovative techniques like swish activation functions and the Giant Trevally Optimizer (GTO) for parameter optimization. Meanwhile, the GTO, inspired by the movement patterns of the Giant Trevally fish, provides efficient and effective parameter optimization, improving the model’s convergence speed and accuracy. Comparative analysis against recent existing models reveals superior performance for both the LMD-full MIDI and Reddit MIDI datasets, with impressive metrics including inception scores of 9.36 and 2.98, Fréchet inception distances of 35.29 and 135.54 and accuracies of 99.98% and 99.95%, respectively. The DIWFA-GAN significantly outperforms existing models in generating high-fidelity melodies, as evidenced by superior inception scores, Fréchet inception distances, and accuracies on both datasets.

Systematic Literature Review: Mathematical Literacy Skills in Terms of Mathematics Learning Motivation

Mathematical literacy and motivation to learn mathematics are two important aspects of education. Mathematical literacy enables students to understand and apply mathematical concepts in everyday life, as well as think logically and solve problems. Mathematics learning motivation influences students' effort and perseverance in learning the material, improving academic interest and performance. The combination of the two is essential for educational success and the development of critical thinking skills required in the modern world. The objectives of research generally cover the following aspects Measuring Mathematics Literacy Level, Assessing Mathematics Learning Motivation, Identifying the Relationship between Mathematics Literacy and Learning Motivation, Recognizing Barriers and Challenges, Developing Effective Learning Strategies. This research uses the SLR (Systematic Literature Review) method by reviewing 16 articles. Data collection in this study was carried out by reviewing all articles related to Mathematical Literacy Ability, Learning Motivation, Mathematical Literacy Ability in terms of Learning Motivation published from 2019 to 2023. Based on the results of the study, it was found that motivation to learn mathematics plays an important role in students' mathematical literacy skills. Students with low motivation tend to learn by force, so their mathematical literacy skills are low because they tend to do problems procedurally without in-depth analysis. The implication is the need for motivational strategies, curriculum design, teacher training, literacy programs, and parental involvement.

You say you can, but can you? The impact of entrepreneurship education on unwarranted and gendered entrepreneurial self-efficacy - a calibration study

PurposeEntrepreneurial self-efficacy (ESE) has a dark side largely ignored in the field of entrepreneurship education. Research in educational psychology indicates that self-efficacy is prone to misjudgment, with novice learners often displaying overconfidence. Furthermore, this misjudgment is gendered; studies suggest that men are more likely to display overconfidence and less likely to correct erroneous self-assessments. However, realistic self-assessments are essential for effective learning strategies, pivotal for performance in the ambiguous entrepreneurial context. Therefore, this study explores whether entrepreneurship education helps mitigate overconfidence, and if this impact varies by gender.Design/methodology/approachCommon in educational psychology, but new in the field of entrepreneurship education, a calibration design captures discrepancies between perceived and actual performance. Data from before and after an introductory undergraduate entrepreneurship course (N = 103) inform descriptive analyses, statistical comparison tests and calibration plots.FindingsAs expected, nearly all novice students showed significant overconfidence. Curiously, gender difference was only significant at the end of the course, as overconfidence had decreased among female students and increased among male students.Originality/valueThe paper advocates a more nuanced stance toward ESE, and introduces ESE accuracy as a more fitting measure of entrepreneurial overconfidence. The findings flag the common use of self-perception as a proxy for actual competence, and evoke new research avenues on (gender differences in) learning motivations of aspiring entrepreneurs. Finally, the study shares guidance for entrepreneurship educators on fostering a “healthier” level of self-efficacy for better entrepreneurial learning.

Ungrading’s Impact on Learning and Autonomy: Insights from an Empirical Study

Library and Information Science (LIS) is an interdisciplinary field that integrates principles from various disciplines, including computer science and the humanites, positioning itself uniquely within STEM. This paper explores the adoption of ungrading in STEM-focused LIS courses and challenges grading paradigms to foster more inclusive and effective learning environments. Through a mixed-methods study involving thirteen graduate students, the research examines the impact of ungrading on student engagement, learning effectiveness, and perceptions of the learning environment. The research is ongoing, but preliminary findings suggest that ungrading reduces stress, shifts focus towards mastery, supports interest-driven learning, and promotes student responsibility for their own learning. The effects align with Universal Design for Learning (UDL) principles, suggesting that ungrading can enhance educational access and equity. This study contributes to the discourse on pedagogical innovation in LIS education and advocates for a shift towards assessment methods that emphasize learning and improvement over traditional grading schemes.

문제중심학습 교육이 간호대학생의 문제해결능력, 자기주도 학습능력, 임상추론역량에 미치는 효과

Objectives The purpose of this study was to determine the effect of problem-based learning education on problem-solving ability, self-directed learning ability, and clinical reasoning competency of nursing students. Methods The research design is a quasi-experimental study with a single-group before/after design. A preliminary survey was conducted on April 3 and 4, 2024, targeting 55 fourth-year nursing students, and a follow-up survey was conducted on April 24 and 25. Data analysis included descriptive statistics, paired t-test, and Pearson correlation analysis using the SPSS Statistics 22.0 program. Results After problem-based learning education, nursing students' problem-solving ability(t=-5.91, p<.001), self-directed learning ability(t=-6.02, p<.001), and clinical reasoning ability(t=-7.39, p<.001) was statistically significantly improved. Conclusions Through this study, it was confirmed that problem-based learning is an effective teaching and learning method in improving nursing students' problem-solving ability, self-directed learning ability, and clinical reasoning competency. Therefore, efforts should be made to strengthen the capabilities of nursing students by expanding subjects that apply problem-based learning in nursing education.

The Effect of Observational Learning and Word of Mouth Learning on Consumer Behaviors

This article explores two learning methods of social interaction in social media and e-commerce environments: observational learning and word-of-mouth learning, and their impact on consumer behavior. This article summarize the influence of two learning methods on consumer behavior in social interaction, and their differences. The article found that both observational learning and word-of-mouth learning have a significant impact on consumer behavior, with positive observational learning having a clear effect on information., Negative word-of-mouth learning information has a stronger influence on consumer decision-making. Observational learning enhances external motivation, while word-of-mouth learning stimulates internal motivation. When highly involved in product decision-making, word-of-mouth details are more critical; Low involvement products allow for more effective observation and learning of information. The impact of word-of-mouth learning on long-term decision-making increases over time. Observing and learning information spreads quickly, while word-of-mouth information spreads slowly. Understanding these mechanisms is crucial for e-commerce platforms and sellers to develop marketing strategies.

The Interactive Effects of Video Type and Viewing Device on Pre-service Teachers’ Learning Performance

Classroom video use in teacher education is rising, but the interplay of video type (2D, panoramic) and viewing device (PC, HMD) on learning remains unexplored. This study examined the interactive effects of video type (2D, panoramic) and viewing device (PC, Head-Mounted Display [HMD]) on pre-service teachers’ learning performance. 143 pre-service teachers from a China university participated in a 2 × 2 randomized controlled experiment, viewing a 10-minute instructional video. Results indicate that panoramic video with HMD yielded the best learning outcomes, enhancing academic achievement, attention, presence, and immersion. Conversely, 2D video on HMD increased cognitive load. Interestingly, while PC-viewed panoramic video maximized attention, it also generated the highest cognitive load. Focus group interviews revealed the potential of immersive learning alongside challenges like motion sickness and navigation difficulties. This research provides empirical evidence for the interaction of video type and viewing devices in teacher education, informing the design of effective video-based learning.

Effectiveness of Online and Offline Learning: Comparative Study at English Education Department University of Mataram

This thesis aims to find the effective implementations between online and offline learning and determine which learning mode is effective at the University of Mataram. This study focused on comparing the effectiveness of different modes of learning implementations based on students’ perceptions. The subject of this study is the students at the English Education Department University of Mataram who had experience with online, offline, and blended learning in the class. The researcher analyzes data using mixed methods (qualitative and quantitative) according to Sugiyono (2017). In this thesis researcher chose the sixth semester, that frequently used between online and offline learning with five classes, and chose one class to observe consisting of 27 students, the researchers collected the data using two different instruments, there are questionnaires researcher collected data related to the effectiveness of online and offline learning using a closed-ended questionnaire and the second one is an interview that’s researcher interviewed some students to know about students' perceptions of online and offline learning in the class. The result that the researcher compared was that offline learning was perceived to be a more effective learning mode this is shown by the higher agreement percentage in key aspects such as syllabus (58.3%), teaching method (44.4%), and discussion (48.1%). Moreover, the implementation of offline and online learning has various aspects in the learning process that can help a teacher and researcher in the future explore more pedagogical strategies and instruction design principles that promote effective offline and online learning experiences.

Community college student perceptions of digital anatomy models as a curricular resource.

Digital model platforms and applications are common in anatomy education and continue to grow in number, which suggests that educators and students find use for these tools despite the lack of widely accepted best practices. Consequently, it is a challenge for educators to mindfully integrate digital models into curriculum. This short-term, longitudinal study investigated the effects of integrating a monoscopic digital model as a teaching tool during lectures on reproductive and endocrine anatomy as an intervention in a community college human anatomy and physiology course. Student use and perceptions of digital models were analyzed for correlation with the nature of the course content and the intervention (n = 92). Academic content significantly affected self-reported student use (p < 0.001) as well as student perceived usefulness of the model (p = 0.02). These findings support the conjecture that digital anatomy models may be better for achieving certain specific learning goals opposed to all learning goals. Integration of digital models as an instructional method did not consistently influence student behavior but it made a difference in participant ability to recognize this technology outside of the lecture. Overall, participants had a positive perception of digital models, although they were not perceived as more important than all other curricular resources. Inclusion of monoscopic digital models for teaching anatomy should be considered by educators since teaching with digital models can demonstrate strengths and weaknesses for students within the context the of learning objectives, assisting students to make more informed decisions about effective learning tools.