Stream Classes Research Articles

Research on the influence of perceived quality on users' continuance usage intention of online live streaming class platforms: the mediating role of flow experience and the moderating impact of perceived usefulness.

With the penetration of the "Internet+" into social life, the digitization of education has become a trend and national demand. Alongside the rise of the "Everyone Live Streaming" era, online live streaming class platforms have rapidly grown due to favorable user experiences. Grounded in the Expectation Confirmation Theory, this study employed questionnaire surveys to investigate the influence mechanism of perceived quality, flow experience, and perceived usefulness on individuals' continuance usage intention of online live streaming class platforms. Through the analysis of 773 survey responses, this study reveals several key findings. Firstly, perceived quality significantly and positively affects users' intention to continue using the online live streaming class platforms. Secondly, flow experience partially mediates the relationship between perceived quality and continuance usage intention, underscoring its significance in user decision-making. Additionally, Perceived usefulness negatively moderates the relationship between perceived quality and flow experience, demonstrating varied effects. On the one hand, online live streaming platforms should actively invest in improving the quality of user perception, as this can lead to a better user flow experience and continued willingness to use. On the other hand, they should also pay more attention to the user's flow experience, which has a direct impact on the user's propensity to continue to use. Besides, the perceived usefulness of the online live class by the user should also be taken seriously.

An ensemble learning method with GAN-based sampling and consistency check for anomaly detection of imbalanced data streams with concept drift.

A challenge to many real-world data streams is imbalance with concept drift, which is one of the most critical tasks in anomaly detection. Learning nonstationary data streams for anomaly detection has been well studied in recent years. However, most of the researches assume that the class of data streams is relatively balanced. Only a few approaches tackle the joint issue of imbalance and concept drift. To overcome this joint issue, we propose an ensemble learning method with generative adversarial network-based sampling and consistency check (EGSCC) in this paper. First, we design a comprehensive anomaly detection framework that includes an oversampling module by generative adversarial network, an ensemble classifier, and a consistency check module. Next, we introduce double encoders into GAN to better capture the distribution characteristics of imbalanced data for oversampling. Then, we apply the stacking ensemble learning to deal with concept drift. Four base classifiers of SVM, KNN, DT and RF are used in the first layer, and LR is used as meta classifier in second layer. Last but not least, we take consistency check of the incremental instance and check set to determine whether it is anormal by statistical learning, instead of threshold-based method. And the validation set is dynamic updated according to the consistency check result. Finally, three artificial data sets obtained from Massive Online Analysis platform and two real data sets are used to verify the performance of the proposed method from four aspects: detection performance, parameter sensitivity, algorithm cost and anti-noise ability. Experimental results show that the proposed method has significant advantages in anomaly detection of imbalanced data streams with concept drift.

Products, Polynomials and Differential Equations in the Stream Calculus

We study connections among polynomials, differential equations, and streams over a field 𝕂, in terms of algebra and coalgebra. We first introduce the class of (F,G) - products on streams, those where the stream derivative of a product can be expressed as a polynomial function of the streams and their derivatives. Our first result is that, for every (F,G) -product, there is a canonical way to construct a transition function on polynomials such that the resulting unique final coalgebra morphism from polynomials into streams is the (unique) commutative 𝕂-algebra homomorphism—and vice versa. This implies that one can algebraically reason on streams via their polynomial representation. We apply this result to obtain an algebraic-geometric decision algorithm for polynomial stream equivalence, for an underlying generic (F,G) -product. Finally, we extend this algorithm to solve a more general problem: finding all valid polynomial equalities that fit in a user specified polynomial template.

CBS Kullanarak Akarsu Yönetimi İçin Havza Özelliklerinin Analizi: Gümüşhane Mikro Havzası Örneği

Aim of study: Topography and climatic conditions have effected in determining the processes of the streams of the micro-watershed. Nowadays, the management plans were made for water and soil protection measures in the basins. 
 Area of study: This study was carried outto characterize and prioritize the streams of the Gumushane upper Harşit micro-watershed using a GIS-based spatial approach. 
 Material and methods: Fundamental watershed characteristics including drainage density, slope, land use types, and stream class were evaluated and interpreted for the Gumushane micro-watershed. Calculatea comprehensive value for each parameter, drainage density (Dd), flow frequency (Fs), slope (S), length of land flow (Lg), and land use (Lu) was used.
 Main results: The drainage density, stream flow frequency, and form factor of the microwatershed are from -4 to 26. Finally, the weighted rankings were summarized, and all micro-watersheds were categorized to five classes based on the risk index as very low risk, low risk, medium risk, high risk, and very high risk. This risk map overlaid to land use type maps in GIS where risk areas were evaluated in the finalrisk results. The 739 ha productive forest area within very high-risk areas was changed to non-risk parameters. 
 Highlights: The carrying capacity of streams was calculated using the stream density of streams in the Gumushane micro-watershed. The risk values produced by streams that pass through neighborhoods where land use values for preventing erosion are present.

The infinite-horizon investment–consumption problem for Epstein–Zin stochastic differential utility. II: Existence, uniqueness and verification for vartheta in (0,1)

In this article, we consider the optimal investment–consumption problem for an agent with preferences governed by Epstein–Zin (EZ) stochastic differential utility (SDU) over an infinite horizon. In a companion paper Herdegen et al. (Finance Stoch. 27:127–158, 2023), we argued that it is best to work with an aggregator in discounted form and that the coefficients R of relative risk aversion and S of elasticity of intertemporal complementarity (the reciprocal of the coefficient of elasticity of intertemporal substitution) must lie on the same side of unity for the problem to be well founded. This can be equivalently expressed as vartheta := frac{1-R}{1-S} >0.In this paper, we focus on the case vartheta in (0,1). The paper has three main contributions: first, to prove existence of infinite-horizon EZ SDU for a wide class of consumption streams and then (by generalising the definition of SDU) to extend this existence result to any consumption stream; second, to prove uniqueness of infinite-horizon EZ SDU for all consumption streams; and third, to verify the optimality of an explicit candidate solution to the investment–consumption problem in the setting of a Black–Scholes–Merton financial market.

The effect of critical thinking-infused paragraph writing instruction on university first-year students’ intellectual traits

The purpose of this study was to investigate the effect of critical thinking-infused paragraph writing instruction on enhancing university first-year L2 students’ intellectual traits. The study involved two randomly selected first-year Social Science stream classes. The researchers employed the embedded design in the study because they mainly used quantitative data augmented by qualitative data. The researchers analyzed the questionnaire data and the interview data using the one-way between groups ANCOVA and thematic analysis method respectively. The finding of the questionnaire data analysis indicated that participants in the treatment group were better in their intellectual traits scores. The result of the interview data analysis also revealed that participants in the treatment group had a better interest in using elements of thought and intellectual traits after the intervention. Hence, integrating critical thinking instruction into APW lessons needs to be considered among all stakeholders to enhance university first-year EFL students’ intellectual traits. Keywords: Argumentative paragraph; critical thinking; instruction; intellectual traits; university first-year students.

Projected stream fish community risk to climate impacts in the Northeastern and Midwestern United States

Climate change is expected to alter stream fish habitat potentially leading to changes in the composition and distribution of fish communities. In the Northeastern and Midwestern United States we identified the distribution and characteristics of those fish communities most and least at risk of experiencing changes in climate which deviate from the climate they are associated with. We classified stream fish communities based on a suite of climate and environmental variables with multivariate regression trees under both recent and future conditions based on eight climate models. Our findings showed that some areas, such as the majority of the Illinois, Wisconsin, and Iowa), have high levels of risk of change in stream class, while much of Kentucky, West Virginia, Virginia, Pennsylvania, Eastern Ohio, Southern Michigan, and the Atlantic Coast are at relatively low risk. Stream class shifts ranged from over 75% of segments lost (associated with cooler temperatures) to gains of over 40% (associated with warmer temperatures). Common warmwater species such as green sunfish (Lepomis cyanellus), bluegill (Lepomis macrochirus) and largemouth bass (Micropterus salmoides) are expected to have the largest net gains in associated stream classes, while species associated with cooler streams such as Southern redbelly dace (Chrosomus erythrogaster), slimy sculpin (Cottus cognatus), and Eastern blacknose dace (Rhinichthys atratulus) were expected to experience the largest proportional losses. By pairing our climate risk predictions with other stressors such anthropogenic land use, habitat fragmentation, and water quality impairment, we identified opportunities for preservation (low risk due to all threats), restoration (low risk due to climate, high risk due to other stressors), and adaptation (high climate risk with low risk from other stressors). Understanding which communities are at risk due to climate change will aid in developing adaptation strategies to help sustain them in the future.

Classifying all transducer degrees below N3

Abstract We answer an open question in the theory of transducer degrees initially posed in Endrullis et al. (2016, Proc. Conf. on Developments in Language Theory (DLT 2016), 164–176), on the structure of polynomial transducer degrees. Transducer degrees are the equivalence classes formed by word transformations which can be realized by a finite-state transducer (FST). While there are no general techniques to tell if a word $\sigma $ can be transformed into $\tau $ via an FST, the work of Endrullis et al. (2010, J. Int., 11B.A6, 164–176) provides a test for the class of streams determined by spiralling functions, which includes all streams determined by polynomials. We fully classify the degrees of all cubic polynomial streams which are below the stream corresponding to $n^3$, and many of the methods can also be used to classify the degrees of polynomial streams of higher orders.

Quantifying relations between altered hydrology and fish community responses for streams in Minnesota

BackgroundAltered hydrology is a stressor on aquatic life, but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed on a statewide scale in Minnesota. Best subsets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic metrics (i.e., duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and six categories of biological metrics (i.e., composition, habitat, life history, reproductive, tolerance, trophic) computed from fish-community samples, as well as fish-based indices of biotic integrity (FIBI) scores and FIBI scores normalized to an impairment threshold of the corresponding stream class (FIBI_BCG4). Relations between hydrology and fish community responses were examined using three hydrologic datasets that represented periods of record, long-term changes, and short-term changes to flow regimes in streams of Minnesota.ResultsRegression models demonstrated significant relations between hydrologic explanatory metrics and fish-based biological response metrics, and the five regression models with the strongest linear relations explained over 70% of the variability in the biological metric using three hydrologic metrics as explanatory variables. Tolerance-based biological metrics demonstrated the strongest linear relations to hydrologic metrics. The most commonly used hydrologic metrics were related to bankfull flows and aspects of flow variability.ConclusionsFinal regression models represent paired streamgage records and biological samples throughout the State of Minnesota and encompass differences in stream orders, hydrologic landscape units, and watershed sizes. Presented methods can support evaluations of stream fish communities and facilitate targeted efforts to improve the health of fish communities. Methods also can be applied to locations outside of Minnesota with continuous streamgage data and fish-community samples.

STUDENTS’ PERCEPTION AND PREFERENCE TOWARDS OPEN AND DISTANCE LEARNING (ODL) DURING COVID-19 PANDEMIC: A CASE STUDY OF STUDIO-BASED LEARNING

Open and Distance Learning (ODL) has been widely known to the academic institutions as one of the methods in teaching and learning since COVID-19 pandemic hit nationwide on December 2019. Since then, many educational institutions have started to consider conducting the classes through online platforms such as Google Meet, Cisco WebEx, Microsoft Teams and others. Design-based studio is one of the design stream classes, which practically uses studio classes physically to develop many creative design ideas, skills, innovation, solution, and is considered as the real value of design studio education. However, the studio classes were switched to online platform, and teaching and learning strategy needed to be modified to deal with this issue, dramatically. Thus, the aim of this study is to identify the most effective delivery method in teaching and learning for current best in educational practices. 14 sets of questions in Google Form questionnaire were distributed on week 14 to the students of Landscape Architecture. A total of 261 students responded out of 394 students enrolled in the Landscape Architecture Design studio. The students were in Semester 2, 4 and 6. The students were selected based on the large number of student’s enrollment. The results showed that the students enjoyed learning using Whatsapp, Google Meet and Google Classroom as a synergistic medium for critic sessions. The research suggests three stages of tutorial sessions to suit the needs of the student’s preference.

Predictability of flow metrics calculated using a distributed hydrologic model across ecoregions and stream classes: Implications for developing flow–ecology relationships

AbstractDeveloping environmental flow standards requires an empirical understanding of the relationship between species' ecology and instream flow. However, when congruent biological and hydrologic data are lacking, the accurate simulation of hydrologic metrics (HMs) corresponding to the locations of biological data is needed. Methods to predict HMs vary in formulation (i.e., statistical vs. process‐based hydrologic models), ability to simulate HMs across the full range of the hydrologic regime (i.e., magnitude, duration, frequency, rate of change and timing) and ability to transfer HMs from gaged to ungaged locations. Yet, despite the breadth of modelling approaches, less attention has been paid to the variability in HMs associated with each approach. In this study, we apply a distributed hydrologic model to the diverse watersheds of South Carolina to examine the predictability of HMs from simulated daily time series of streamflow across ecoregions, stream classifications and level of human alteration. In doing so, we contextualize the predictability of HMs, giving managers and researchers in South Carolina the flexibility of choosing HMs that are best suited for quantifying flow–ecology relationships based on the location, flow regime components of interest and uncertainty of HMs. We found that at least one HM within each of the five flow regime components (out of a selected subset of 41 non‐redundant HMs) was consistently and accurately predicted across the diverse streams of the study area. We discuss the patterns of predictability related to site characterizations and individual HMs and their implications for developing environmental flow standards.

TAKE HOME MESSAGE FOR M.B.B.S STUDENTS FROM NEWLY INTRODUCED ONLINE CLASSES DUE TO COVID-19 PANDEMIC

BACKGROUND: The internet becomes “information superhighway”. From its inception, it had grown such that it could be accessed from any part of the world. Conventional classroom teaching had been replaced to some extent by online learning. Almost two years of online classes due to lockdown in Corona virus pandemic, helped the students to understand the future learning methodology. OBJECTIVE:To determine the “take home” message for the M.B.B.S students from online classes. METHODOLOGY: Both live and recorded online classes had been introduced during lockdown period. When medical college opened and students were back to classes a survey was undertaken based on the semi structured questionnaire based on google form. Responses were analyzed with Microsoft excel 365 software. RESULT: 143 out of total 200 students responded (72%). 64% students liked recorded classes, according to them, recorded classes could be accessed at a convenient time (44%), repeat watching helped to clear the concepts (34%), easily accessible (53%), video could be shared among the peer groups (61%). Rest of the students preferred live streaming classes. In their opinion, live classes felt like actual class (75%), could directly interact with friends (66%), asking question directly to the teachers (34%), They tried to include in future the following aspects of online learning to ofine classroom teaching, those were: start peer group learning, sharing the useful contents, improvements of technological knowledge and skills, to maintain discipline in the class- there were take home message for the students after long one year of online classes CONCLUSION: It was clear if proper strategy had been taken and if widespread internet connections would be provided the online classes could be effective as classroom teaching.

Using Structure-from-Motion Photogrammetry to Improve Roughness Estimates for Headwater Dryland Streams in the Pilbara, Western Australia

There are numerous situations where engineers and managers need to estimate flow resistance (roughness) in natural channels. Most estimates of roughness in small streams come from humid areas. Ephemeral streams in arid and semi-arid areas have different morphology and vegetation that leads to different roughness characteristics, but roughness in this class of stream has seldom been studied. A lack of high-resolution spatial data hinders our understanding of channel form and vegetation composition. High resolution structure-from-motion (SfM)-derived point clouds allow us to estimate channel boundary roughness and quantify the influence of vegetation during bankfull flows. These point clouds show individual plants at centimetre accuracy. Firstly, a semi-supervised machine learning procedure called CANUPO was used to identify and map key geomorphic features within a series of natural channels in the Pilbara region of Western Australia. Secondly, we described the variation within these reaches and the contribution of geomorphic forms and vegetation to the overall in-channel roughness. Channel types are divided into five reach types based on presence and absence of geomorphic forms: bedrock; alluvial single channel (≥cobble or sand dominated); alluvial multithread; composed of either nascent barforms or more established; stable alluvial islands. Using this reach classification as a guide, we present estimates of Manning’s roughness within these channels drawing on an examination of 650 cross sections. The contribution of in-channel vegetation toward increasing channel roughness was investigated at bankfull flow conditions for a subset of reaches. Roughness within these channels is highly variable and established in-channel vegetation can provide between a 35–55% increase in total channel roughness across all channel types. This contribution is likely higher in shallow flows and identifies the importance of integrating vegetation and geomorphic features into restorative practices for these headwater channels. These results also guide Manning’s selection for these semi-arid river systems and contribute to the vegetation-roughness literature within a relatively understudied region.

Cryptocurrencies: A bibliometric analysis

The purpose of the current paper is to identify influential aspects of published literature and future research questions to set forth future research agenda based on comprehensive literature review using bibliometric and content analysis. The study analyzed 1225 documents from the international Scopus database using bibliometric analysis and content analysis. VOSviewer software is used for bibliometric analysis. The analysis revealed that most of the information was derived from the Finance Research Letters. Moreover, the United Kingdom is the most cited country, while Tianjin University in China has the highest publications affiliations. Furthermore, the analysis shows that the keyword analysis of cryptocurrency literature had four classes of research streams in cryptocurrency, namely, cryptocurrency, Blockchain, Fintech, and currency, representing the most upcoming trends. The present study makes a significant contribution to the literature by providing a framework for future research. The framework provides opportunities to future researchers to explore the web of relations among some identified research streams as future research agenda.

A Comparative Study on Online Teaching Practices in China and South Korea in the Time of COVID-19

The transition from traditional teaching practices to remote education was sped up by the outbreak of COVID-19 pandemic dramatically. The international students who have to stay in their home countries due the travel restrictions rely on the online study. In this manuscript, we examine how the teaching methodology affects the outcome of remote education (e.g., an undergraduate program provided by CUMT, and a graduate program provided by Gachon University). Both SPOC and online streaming classes were evaluated based on the performance of international undergrads majored in chemical engineering. And multiscale simulations were adopted to elucidate the complex transport phenomena in chemical engineering classes to develop a more efficient method for distant engineering education. The preliminary results of this comparative study on online teaching practices indicate that active studies play an important role in online study for international students.

E-learning in Chinese Higher Education During the COVID-19 Pandemic

코로나19의 갑작스런 확산으로 전세계 많은 대학들이 문을 닫고 온라인 교육을 실시하게 되었다. 중국의 경우 코로나19 확산과 더불어 즉각적으로 전통적인 대면수업을 완전한 온라인 학습으로 전환하기 위해 광범위한 조치를 취하였다. 본 연구는 특히 인프라 구축 및 기술 지원, 콘텐츠 개발 및 사용, 교수-학생 상호작용에 초점을 맞춰 코로나19에 대한 중국 고등교육 e-러닝의 현황과 관련 쟁점을 분석하고자 하였다. 이를 위해 중국 정부의 관련 문서와 우수 학술지에 게재된 29편의 자료를 분석하였다. 분석 결과 대학에서는 5G, AI 등 첨단 기술과 PBL, 플립러닝 등 다양한 디지털 콘텐츠, 창의적 교수법을 활용하였고, 실시간 스트리밍 수업을 통하여 이러닝을 지원한 것으로 나타났다. 그럼에도 불구하고, 지역 간의 불균형적인 인프라 구축과 기술 지원, 제한된 콘텐츠 개발 및 온라인 학습 사용, 교수와 학생 간의 효과적인 상호작용 부족에 대한 쟁점들이 여전히 남아 있었다. 본 연구는 이를 바탕으로 낙후된 지역의 기반시설 건설에 더 많은 노력을 기울이고, 교수자에 대한 기술 지원을 적극적으로 하여야 하며, 고등교육 전용 통합 학습관리 시스템을 개발할 것을 제안하였다.Purpose: This paper addressed the current status and issues of e-learning in Chinese higher education during the COVID-19 pandemic, especially focusing on the infrastructure construction and technical support, the contents development and use, and the interactions between instructors and learners. Methods: The literature review and document analysis was used in this study. We analyzed a total of 29 research articles and government documents from Chinese MOE and prestige journals published between 2020 and 2021. Results: The results shown that advanced technology such as 5G and AI, diverse digital contents and creative teaching methods such as PBL and flipped classroom were put into used in universities and colleges to assist e-learning and hence learning effect through the live streaming class. Nevertheless, there remain issues on unbalanced infrastructure construction and technical support between east and west areas, limited content development and usage of e-learning, lack of effective interactions between instructors and learners. Conclusion: E-learning in Chinese higher education made notable progress despite the widespread of COVID-19. The relevant issues were also discussed to promote e-learning.

Stream/block ciphers, difference equations and algebraic attacks

In this paper we model a class of stream and block ciphers as systems of (ordinary) explicit difference equations over a finite field. We call this class “difference ciphers” and we show that ciphers of application interest, as for example systems of LFSRs with a combiner, Trivium and KeeLoq, belong to the class. By using Difference Algebra, that is, the formal theory of difference equations, we can properly define and study important properties of these ciphers, such as their invertibility and periodicity. We describe then general cryptanalytic methods for difference ciphers that follow from these properties and are useful to assess the security. We illustrate such algebraic attacks in practice by means of the ciphers Bivium and KeeLoq.

Quantifying flow–ecology relationships across flow regime class and ecoregions in South Carolina

The natural flow regime (i.e. magnitude, frequency, duration, timing and rate of change of flow events) is crucial for maintaining freshwater biodiversity and ecosystem services. Protecting instream flow from anthropogenic alterations first requires an understanding of the relationship between aquatic organisms and the flow regime. In this study, we used a unique framework based on random forest modeling to quantify effects of natural flow regime metrics on fish and macroinvertebrate assemblages across ecoregions and flow regime types in the state of South Carolina, USA. We found that all components of the natural flow regime affected both fish and benthic macroinvertebrate assemblages, suggesting that maintaining natural aspects of all flow regime components is critical for protecting freshwater diversity. We identified hydrologic metrics and flow regime components such as magnitude, frequency, and duration of flow events, that were associated with the greatest ecological responses for individual stream classes to help managers prioritize hydrologic and biological metrics of interest during environmental flow standard development. The response of aquatic organisms to hydrologic metrics varied across stream classifications and ecoregions, highlighting the importance of accounting for differences in flow regime and ecoregion when designing environmental flow standards. We provide a flexible framework based on statistical flow-ecology relationships that can be used to inform instream flow management and assess effects of flow alteration on riverine assemblages.

Immersive live streaming experience in satisfying the learners’ need for self-directed learning

PurposeThis study aims to examine live streaming experiences of business students’ at the tertiary education level, and how the use of this interactive platform satisfies their affective, cognitive, social and hedonic needs in learning. Likewise, it explored the influence of live streaming class on the learning outcome needed in achieving self-directed learning.Design/methodology/approachDrawing on the uses and gratifications theory, a conceptual framework was developed to discover the impact of interactive live streaming platform in meeting learners’ needs required for self-directed learning. A survey was conducted with a sample of 402 business undergraduate students from 5 universities. Data was analyzed with covariance-based structural equation modeling.FindingsThis study confirmed that learners’ gratifications gained from live streaming encouraged them to collaborate with the instructors in meeting the learning outcomes. The findings also supported that the interactive nature of live streaming offers the opportunity for students to learn independently. Thus, it sheds new light on how a live streaming learning environment can be further developed in promoting self-directed learning.Originality/valueThis study offers a novel understanding of live stream class adoption by examining learners’ needs from a uses and gratification perspective. It also contributed new insight to the existing literature on live streaming technology use in education to promote self-directed learning.

1st MBBS professional student’s perception on teaching & learning methods of anatomy, before and at the time of COVID-19 pandemic

Objectives: COVID-19 pandemic has brought challenges to learn the anatomy subject for the students. Perception & online opinion has been taken from the students of SVS medical college, Mahbubnagar, on teaching and learning methods of anatomy, before and at the time of covid-19 pandemic Materials and Methods: students feedback has been collected through google forms - online survey opinion & Inputs were collected from the 113 MBBS students of the academic year 2019-2020, who had just completed their first year syllabus in both offline and online teaching methods, before lockdown and after lockdown (September-2019 to December-2020). Present study was done by using specially designed questionnaire comprising of points relating to the present curriculum in anatomy & teaching methodology at SVS Medical College, Mahbubnagar. Results: Students point of view, online teaching like streaming (ZOOM MEETING, GOTO MEETING & CISCO WEBEX) was not that much effective. Majority of the students opted for the best method for online teaching was recorded video or voice over PPT’S are the best option than the online streaming classes. Finally the students have opted for Traditional teaching like chalk & talk fallowed by PPT Presentation. Gross anatomy was mainly learned by the dissections involved by the students and faculty side by side. Histology was mainly learned by spending the more time on the microscope & involved in small group teaching. Embryology was mainly understood by small group teaching with the help of 3D models. Conclusion: The study concluded that the chalk and talk teaching fallowed by PPT’S, dissection by the students along with the faculty and spending more time on the microscope with small group teaching were the best methods to approach the anatomy subject. KEY WORDS: Students perception, Anatomy teaching learning methods, online and offline, chalk & talk, dissection.