STUDENT LEARNING APPROACHES OF ARCHITECTURE STUDENTS: DEEP OR SURFACE LEARNING APPROACH

2020 ◽  
Author(s):  
Gabriel Sen ◽  
Albert Adeboye ◽  
Oluwole Alagbe
Keyword(s):  
Student Learning ◽  
Learning Approach ◽  
Learning Approaches ◽  
Surface Learning

Student Learning in an Online Environment

2011 ◽  
pp. 224-234
Author(s):  
Rodney Arambewela
Keyword(s):  
Deep Learning ◽  
Student Learning ◽  
Learning Experience ◽  
Learning System ◽  
Learning Approaches ◽  
Learning Contexts ◽  
Technology In Teaching ◽  
E Learning ◽  
Learning Orientations ◽  
Surface Learning

The increasing class sizes, changing expectations, diversity and mobility of students and the use of computer technology in teaching have challenged universities, world over, to review educational courses and delivery to provide a more satisfying learning experience to students. Understanding how students learn is essential in this process and continuous enquiry into teaching practices for their effectiveness towards enhancement of student learning outcomes is therefore considered a vital strategy. This chapter discusses an exploratory study on the differences in the learning approaches of a group of students in a second year marketing course in an Australian university. E-learning system remains the primary communication and the learning resource of these students. Results indicate that there are no significant differences in the study approaches of students but on average they seem to demonstrate deep learning than surface learning although they may differ in terms of the learning contexts. The study also reveals that in comparison female students and older aged students seem to demonstrate deep learning orientations than surface learning orientations.

In Search of Greater Understanding: The Impact of Mastery Learning on Social Science Education

2020 ◽  
Vol 48 (2) ◽  
pp. 107-119
Author(s):  
Patrick R. Cundiff ◽  
Olivia McLaughlin ◽  
Katherine Brown ◽  
Keiondra Grace
Keyword(s):  
Social Sciences ◽  
Student Learning ◽  
Teaching And Learning ◽  
Mastery Learning ◽  
Relevant Literature ◽  
Learning Approach ◽  
Learning Approaches ◽  
Social Science Education ◽  
Level Of Understanding ◽  
The Impact

Mastery learning approaches were designed to improve student learning and elevate the level of understanding across a broader swath of students. These approaches operate under the belief that all students are capable of learning if given enough time. Little research has examined the utility or applicability of a mastery learning approach for social sciences outside of research methods courses. This study provides a review of the relevant literature on mastery learning, a discussion of the applicability of this approach to the teaching and learning of social sciences, and a review of the process and results of the conversion of more traditionally organized and taught courses to a mastery learning approach. Overall, our evaluation provides evidence that a mastery learning approach can make a significant impact on student learning.

A SMARTPHONE-BASED ADAPTIVE LEARNING APPROACH TO ENHANCE STUDENTS’ LEARNING OUTCOMES IN ENGLISH SUBJECT

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Farhanirahma ◽  
Lidiyatul Izzah ◽  
Muhamad Sofian Hadi
Keyword(s):  
Student Learning ◽  
Learning Outcomes ◽  
Adaptive Learning ◽  
Test Group ◽  
Student Learning Outcomes ◽  
Learning Approach ◽  
Learning Approaches ◽  
Mean Values ◽  
Significance Level ◽  
Post Test

The purpose of this study is to improve student learning outcomes through a smartphone-based adaptive learning approach to 28 students from the 11th grade students in the 2020/2021 academic year. It is important to consider the educational context when evaluating the barriers to adopting adaptive learning approaches on digital platforms. The method used in this study is a quantitative method, everything observed was measured and converted into numbers so that statistical analysis techniques were possible. The author chose  a pre-experimental design with a pre-test post-test group design, in which a group of subjects is taken from a certain population and performed in a pre-test and then undergoes treatment one after another. After the treatment, the person received a posttest to measure the learning outcomes of the group. The grades given have the same weight. The difference between the results of the pretest and the post-test shows the results of the treatment performed. The results of this study were analyzed using the t-test by comparing the mean values of the pre-test and post-test. The results showed that the t-observation value (7.8) was higher than the t-table value (1.70562) at the 5% significance level. It can be concluded that the learning approach adaptive smartphone-based improves student learning outcomes in English subjects.

scholarly journals Identifier les attitudes des étudiants en géographie après leurs études secondaires

2009 ◽  
Vol 38 (1) ◽  
Author(s):  
Burckin Dal
Keyword(s):  
Higher Education ◽  
Deep Learning ◽  
Student Learning ◽  
Education Student ◽  
Learning Approach ◽  
Learning Approaches ◽  
Premier Cycle ◽  
Degree Of Confidence ◽  
One Year

Ce travail expose les résultats d’une étude réalisée dans le but d’analyser la démarche d’apprentissage d’un groupe d’étudiants de premier cycle de géographie. Seront traitées ici les démarches d’apprentissage qu’ils adoptent et la façon dont évolue leur niveau de confiance en soi après un an d’enseignement supérieur. Les étudiants étaient confrontés à un programme visant au développement des capacités dans le cadre de la géographie, qui mettait l’accent sur une démarche d’apprentissage en profondeur. Les résultats montrent que, bien que leur niveau de confiance en leur capacité d’étudier et d’apprendre ait augmenté, leur démarche d’apprentissage est devenue de plus en plus instrumentale. This paper shows the results of a study carried out in order to analyse the learning approach in geography of cohorts of students on entry to a geography degree. After one year of higher education, student learning approaches and their degree of confidence are examined. A program aimed at the development of the learning capacities based on a deep learning approach was proposed to students. The results indicate that although their degrees of confidence in their capacity to study increased, their learning approaches became increasingly instrumental.

scholarly journals The Differences of the Student Learning Outcome Using Realistic Mathematics Learning Approaches (PMR) And Contextual Learning Approaches (CTL) on the Sets Material

2018 ◽  
Vol 9 (1) ◽  
pp. 63
Author(s):  
Nurina Kurniasari Rahmawati ◽  
Amah Amah
Keyword(s):  
Student Learning ◽  
Hypothesis Test ◽  
Mathematics Learning ◽  
Sampling Technique ◽  
Learning Outcome ◽  
Contextual Learning ◽  
Learning Approach ◽  
Learning Approaches ◽  
Realistic Mathematics ◽  
Student Learning Outcome

This research aims to determine differences in learning outcomes of students who use Realistic Mathematics Learning (PMR) and Contextual Approach (CTL) approaches on the set Material. This research method is quasi experiment with posttest only control design. The sampling technique was used cluster random sampling with 2 experimental classes These are experimental class 1 (the class was treated with the Realistic Mathematics Education (PMR) approach and experimental class 2 (the class was treated with the Contextual Learning (CTL) approach The hypothesis test is used the t-test. The results of the research is found that there were differences between the student learning outcome in the set material using Realistic Mathematics Learning (PMR) approach and the student learning outcome in the set material using the Contextual Learning approach (CTL). Because the student learning outcome in the set material using Realistic Mathematics Learning (PMR) approach better than the student learning outcome in the set material using the Contextual Learning approach (CTL).

scholarly journals Preferences for deep-surface learning: A vocational education case study using a multimedia assessment activity

2010 ◽  
Vol 26 (7) ◽  
Author(s):  
Simon Hamm ◽  
Ian Robertson
Keyword(s):  
Deep Learning ◽  
Approaches To Learning ◽  
Management Program ◽  
Learning Preferences ◽  
Learning Approach ◽  
Learning Approaches ◽  
Structured Interviews ◽  
Assessment Activity ◽  
Surface Learning ◽  
Deep And Surface Learning

<span>This research tests the proposition that the integration of a multimedia assessment activity into a Diploma of Events Management program promotes a deep learning approach. Firstly, learners' preferences for deep or surface learning were evaluated using the revised two-factor Study Process Questionnaire. Secondly, after completion of an assessment exercise comprising a multimedia presentation with digital images and oral commentary, the respondents' self-described approaches to learning were collected using semi-structured interviews. Using these two data sets, learners preferred and implemented learning approaches were compared. Results show that whilst the multimedia assessment exercise did not prohibit the adoption of a deep learning approach, it tended to enable the adoption of both deep and surface learning approaches. In addition to informing our understanding of the relationship between deep and surface learning preferences and the implementation of a multimedia assessment item, the data gathered also provide some clues related to the sorts of factors that the respondents considered and how they responded to these factors in their undertaking of the assessment exercise.</span>

scholarly journals PENERAPAN PENDEKATAN PEMBELAJARAN MATEMATIKA REALISTIK TERHADAP KEMAMPUAN PEMECAHAN MASALAH MATEMATIS SISWA

2020 ◽  
Vol 1 (2) ◽  
pp. 78-84
Author(s):  
Ade Evi Fatimah
Keyword(s):  
Problem Solving ◽  
Student Learning ◽  
Learning Process ◽  
Teaching And Learning ◽  
Mathematics Learning ◽  
Descriptive Analysis ◽  
Learning Activities ◽  
Learning Approach ◽  
Learning Approaches ◽  
Realistic Mathematics

Realistic mathematics learning is learning that connects and engages the surrounding environment and real experiences that students have experienced in everyday life. The objectives of this study were (1) to find out how to apply realistic mathematics learning approaches to students' problem-solving abilities in fractions material. (2) To determine student learning activities on the application of realistic mathematics learning approaches to students' problem-solving abilities on fraction material. This study uses a descriptive analysis. The subjects in this study were 7th-grade students of SMP Tunas Pelita Binjai, while the objects in this study were the students' problem-solving abilities and student activities during learning. Based on the results of the analysis, it was obtained (1) The application of a realistic mathematics learning approach to students' problem-solving abilities on fractions in Grade 7 was to present contextual problems about fractions, solve contextual problems about fractions, then compare and discuss answers and conclude learning. Based on the learning process, a percentage of 80.55% of students obtained problem-solving abilities above the low category. This shows that the realistic mathematics approach is effective for building students 'problem-solving abilities. (2) Student learning activities on the application of realistic mathematics learning approaches to students' problem-solving abilities on fraction material in Grade 7 are in the good category with a final score of 80.14. So it can be suggested that in the teaching and learning process it is expected that the teacher uses a realistic mathematics learning approach.

The Effect of Jigsaw Methode and Motivation on Students’ of Learning Outcomes

2020 ◽  
Vol 3 (1) ◽  
pp. 20-30
Author(s):  
Yunita Yunita ◽  
Hidayat Hidayat ◽  
Harun Sitompul
Keyword(s):  
Cooperative Learning ◽  
Student Learning ◽  
Learning Outcomes ◽  
Student Learning Outcomes ◽  
Learning Motivation ◽  
Learning Approaches ◽  
High Learning ◽  
Average Value ◽  
The Difference ◽  
Low Motivation

This study aims to: (1) investigate the effect of Jigsaw cooperative learning on students learning outcomes; (2) find the difference in learning outcomes between high and low learning motivation and (3) find the interaction between learning approaches and learning motivation towards learning outcomes. The population of the study is students of grade IVa, IVb, IVc at SD Kasih Ibu Patumbak and the sample in this study is grade IVa with 35 students and grade IVb with 35 students. The results show that: (1) the average student learning outcomes of jigsaw cooperative learning is 28.40 while conventional is 24.14. Thus, students learning outcomes that get cooperative learning of jigsaw type are higher than conventional learning, (2) Students who have high motivation get an average value = 30.74, while low motivation is 22.72. Thus, it can be concluded that there are differences in student learning outcomes having high learning motivation and low learning motivation, and (3) students learning outcomes  taught by jigsaw cooperative learning are high learning motivation groups (32.94), and low learning motivation groups (24.58), while students taught with conventional learning are high learning motivation groups (28.40 ), and low motivation groups (20,95). Thus, there is no interaction between learning approaches and learning motivation towards learning outcomes.

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

2017 ◽  
Author(s):  
Sabrina Jaeger ◽  
Simone Fulle ◽  
Samo Turk
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Supervised Machine Learning ◽  
Learning Approach ◽  
Learning Approaches ◽  
Unsupervised Machine Learning ◽  
Feature Representations ◽  
Machine Learning Approach ◽  
The Individual ◽  
Vector Representations

Inspired by natural language processing techniques we here introduce Mol2vec which is an unsupervised machine learning approach to learn vector representations of molecular substructures. Similarly, to the Word2vec models where vectors of closely related words are in close proximity in the vector space, Mol2vec learns vector representations of molecular substructures that are pointing in similar directions for chemically related substructures. Compounds can finally be encoded as vectors by summing up vectors of the individual substructures and, for instance, feed into supervised machine learning approaches to predict compound properties. The underlying substructure vector embeddings are obtained by training an unsupervised machine learning approach on a so-called corpus of compounds that consists of all available chemical matter. The resulting Mol2vec model is pre-trained once, yields dense vector representations and overcomes drawbacks of common compound feature representations such as sparseness and bit collisions. The prediction capabilities are demonstrated on several compound property and bioactivity data sets and compared with results obtained for Morgan fingerprints as reference compound representation. Mol2vec can be easily combined with ProtVec, which employs the same Word2vec concept on protein sequences, resulting in a proteochemometric approach that is alignment independent and can be thus also easily used for proteins with low sequence similarities.

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