scholarly journals Temporal analysis of academic performance in higher education before, during and after COVID-19 confinement using artificial intelligence

2021 ◽  
Author(s):  
Laia Subirats ◽  
Aina Palacios Corral ◽  
Sofia Perez-Ruiz ◽  
Santi Fort ◽  
Gomez Monivas Sacha
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Field Experiment ◽  
Learning Strategies ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Final Exam ◽  
Self Evaluation ◽  
Continuous Basis ◽  
The Mean

This study provides the profiles of students and a regression prediction of marks considering data before, during, and after the COVID-19 pandemic. Using a field experiment of 396 students and more than 7400 instances, we have studied the differences in performance considering the temporal distribution of autonomous learning during courses from 2016/2017 to 2020/2021. After applying unsupervised learning, results show 3 profiles of students: continuous students, last-minute students, intense and last-minute students. We have found that the highest success ratio is related to students that work in a continuous basis. However, last minute working is not necessary linked to failure. After applying regression, results show that the mark of the students can be predicted successfully and that the most relevant values are the mean mark in self-evaluation obtained the month before the final exam, the mean mark two months before, the number of attempts two months before and the number of attempts the month before. Results are a little worse but still acceptable if the prediction wants to be made a month before the final exam. This regression is useful to prevent students' wrong learning strategies, and (more effective) to detect malpractices such as copying. We have done all these analysis taking into account the effect of the COVID-19 pandemic, including also a discussion about which factors will be extended in time and which ones are transitory and only due to the confinement.

scholarly journals Influence of COVID-19 confinement in students’ performance in higher education

2020 ◽  
Author(s):  
Teresa Gonzalez ◽  
Mariángeles de la Rubia ◽  
Kyle Hincz ◽  
Marta Comas Lopez ◽  
Laia Subirats ◽  
...  
Keyword(s):  
Higher Education ◽  
Field Experiment ◽  
Learning Strategies ◽  
Learning Performance ◽  
Significant Positive Effect ◽  
Face To Face ◽  
Continuous Basis ◽  
Group Control ◽  
Positive Effect ◽  
Assessment Activities

This study explores the effects of COVID-19 confinement in the students’ performance in higher education. Using a field experiment of 458 students from three different subjects in Universidad Autónoma de Madrid (Spain), we study the differences in assessments by dividing students into two groups. The first group (control) corresponds to academic years 2017/2018 and 2018/2019. The second group (experimental) corresponds to students from 2019/2020, which is the group of students that interrupted their face-to-face activities because of the confinement. The results show that there is a significant positive effect of the COVID-19 confinement on students’ performance. This effect is also significative in activities that did not change their format when performed after the confinement. We find that this effect is significative both in subjects that increased the number of assessment activities and subjects that did not change the workload of students. Additionally, an analysis of students’ learning strategies before confinement shows that students did not study in a continuous basis. Based on these results, we conclude that COVID-19 confinement changed students’ learning strategies to a more continuous habit, improving their efficiency. For these reasons, better scores in students’ assessment are expected due to COVID-19 confinement that can be explained by an improvement in their learning performance.

scholarly journals Patterns and trends in engineering education in sustainability

2019 ◽  
Vol 20 (2) ◽  
pp. 360-377 ◽  
Author(s):  
Gemma Tejedor ◽  
Martí Rosas-Casals ◽  
Jordi Segalas
Keyword(s):  
Higher Education ◽  
Engineering Education ◽  
Learning Strategies ◽  
Keyword Search ◽  
Temporal Analysis ◽  
Education For Sustainability ◽  
Future Research ◽  
Content Type ◽  
The Past ◽  
Sustainability In Higher Education

Purpose This paper aims to identify patterns and trends taking place in engineering education in sustainability, through analyzing the evolution of research conducted in relevant publications in the field of engineering education for sustainability in the past decades. Design/methodology/approach First, a bibliometric approach has been applied, adopting a co-word analysis based on co-occurrence of the keywords (300 items) in articles from three indexed journals related to engineering, education or sustainability. The selection of the articles has been based on the appearance of the previous three terms in the topic and title fields of the journal, where journal scope (based in the categories of the InCites Journal Citation Reports) covered at least two topics, and the third topic was applied in the search, as follows: International Journal of Sustainability in Higher Education – Scope of the journal: sustainability and education, Keyword search: engineering (20 papers); Journal of Cleaner Production – Scope of the journal: sustainability and engineering, Keyword search: education (122 papers); International Journal of Engineering Education – Scope of the journal: engineering and education, Keyword search: sustainability (29 papers); Second, to identify topological patterns and their evolution, a structural and temporal analysis of the network of keywords and a categorization of the keywords in thematic clusters (named categories) have been performed. Findings The most relevant categories in terms of corresponding number of keywords, even though these have decreased in recent years, are those related with institutional and policy aspects to embedding or applying sustainability in higher education. At the same time, categories related to the professional development of faculty members, implementation and use of learning strategies (i.e. real-world learning experiences, educational innovative initiatives/tools/techniques) and cross-boundary schemes (i.e. transdisciplinarity, ethics, networking, etc.) increase their relevance in the past five years, signaling some of the challenging fields of interest in engineering higher education in sustainability in the near future. Practical implications Knowledge of the trends in devising sustainability education in engineering allows for designing curricular schemes and learning strategies to achieve competences, which are key factors for the change toward sustainability. Originality/value This research has a strong strategic value, as it indicates the focus of future research efforts and networking on some of the topics of greatest concern in engineering higher education for sustainability.

scholarly journals Cultivation of Student Translator Autonomy in UK Higher Education

2021 ◽  
Vol 14 (5) ◽  
pp. 41
Author(s):  
Xiaoqing Fang ◽  
Philip Morris
Keyword(s):  
Higher Education ◽  
Learning Strategies ◽  
Goal Setting ◽  
Quality Criteria ◽  
Task Completion ◽  
Self Reflection ◽  
Self Evaluation ◽  
Translation Quality ◽  
The Uk ◽  
Uk Higher Education

This study, based on two questionnaires directed to translation lecturers in UK Higher Education (HE), aims to explore the teacher awareness of learner autonomy in the UK university translation classroom, and the extent to which students of translation are encouraged to become autonomous learners. It covers six aspects of translation education, i.e., objective setting, learning strategies, resources, technology, learner reflection and assessment, and teacher’s role. The results provide insights to the teachers’ understanding of student choice, control and responsibility in autonomous translation learning. The findings suggest that the translation students in UK HE are offered the most choice in translation resources and technologies, and the least choice in co-deciding translation syllabi, specialized professional goal and teaching materials; they seem to share consistent control with their teachers over the whole learning process, from goal-setting, to translation task completion, group collaboration, final version and translation quality criteria decision, to self-evaluation and reflection; they are encouraged to take responsibility for their translation products, collaboration in class, for learning to translate, and learning to evaluate and reflect. Nevertheless, the importance of encouraging student self-evaluation, peer-evaluation and self reflection in UK translation education seems to be underestimated, and is recommended to be brought to the forefront of further research.

scholarly journals Influence of COVID-19 Pandemic in Students’ Distribution of Time in Distant Learning

2021 ◽  
Author(s):  
Pilar Rodriguez ◽  
Santiago Atrio ◽  
Gomez Monivas Sacha
Keyword(s):  
Statistical Analysis ◽  
Learning Strategies ◽  
Learning Strategy ◽  
Final Exam ◽  
Face To Face ◽  
Self Evaluation ◽  
Distant Learning ◽  
Students First ◽  
Learning Scenarios ◽  
Time Parameters

Statistical analysis offers unprecedented opportunities to identify learning strategies. This fact has been boosted in the COVID-19 pandemic because of the data obtained in distant learning scenarios due to the confinement. This article deals with the identification of students’ strategies in different distant learning scenarios such as working autonomously as a support for face-to-face classes or learning autonomously in COVID-19 confinement. We have measured the influence of parameters such as the time they spent in self-evaluation, the scores obtained through this process and the distribution of time when studying autonomously. We have only detected significant results that guide to a better learning strategy when we include time parameters, such as the time between studying sessions or the time between students’ first session and their final exam. We demonstrate that students that started to study earlier and more dispersed get better success ratio (not necessarily better scores) than those that started later and do it more concentrate. The findings from this study suggest that the same amount of time spent in autonomous learning optimizes its effectiveness when it is extended in time. This learning strategy was found more often in COVID-19 confinement, where students were forced to stay at home.

Pengelolaan Data Terintegrasi Berdasarkan Instrumen Akreditasi Perguruan Tinggi 3.0 Menggunakan Zachman Framework

2020 ◽  
Vol 4 (6) ◽  
Author(s):  
Ardhin Primadewi ◽  
Mukhtar Hanafi
Keyword(s):  
Higher Education ◽  
Self Evaluation ◽  
The Core ◽  
Depth Analysis ◽  
Performance Report ◽  
Total Data ◽  
Zachman Framework ◽  
The Government ◽  
Data Gap ◽  
Education Performance

Higher education in Indonesia is regulated by the government with the Higher Education Accreditation (APT). In APT 3.0, Higher Education is required to be able to present performance data in the form of a Higher Education Performance Report (LKPT) as a reference in making a Self-Evaluation Report (LED). However, it is necessary to have an in-depth analysis to determine the gaps in the data required by Higher Education according to the APT 3.0 standard. The process of integrating the samples refer to the Zachman Framework (ZF). The results of this simplification that the data is available in support of APT 3.0 approximately 79% of the total data both inside and outside the core business of Higher Education and is well managed in an integrated database. The remaining 21% of the data that are not available is spread across several information systems, especially SIMMawa, SIMHumas and Cooperation, and SIMAKU. This shows that the change in accreditation standards that have been in effect since April 2019 has created a significant data gap for Higher Education. This research also produced an alternative model of integrated data management that can be used as input for Information System developers in the Higher Education scope.

Tendencias del cambio climático en la Demarcación Hidrográfica de Manabí

2018 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Campos Cedeño Antonio Fermín ◽  
Mendoza Álava Junior Orlando
Keyword(s):  
El Niño ◽  
El Nino ◽  
Technical Information ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Botanical Garden ◽  
Monthly Precipitation ◽  
Water Network ◽  
Monthly Distribution ◽  
Index Terms

Abstract— The Manabí Hydrographic Demarcation (DHM) is characterized as the only one that does not receive input from Andes Mountains, therefore, its water network is fed exclusively by the rainfall that occurs in the rainy season and that the warm current of El Niño plays a fundamental role in its production. In order to have technical information, important for the planning, control and development of the water resources of the DHM, in this research is made a temporal analysis of the monthly precipitation for 55 years, period 1963-2017. The National Institute of Hydrology and Meteorology of Ecuador (INAMHI) in station M005, located in the Botanical Garden of the Technical University of Manabí (Universidad Técnica de Manabí) in Portoviejo, obtained these records. An analysis is made of the monthly and annual patterns, establishing that the El Niño events that occurred in 1983, 1997 and 1998, have set guidelines for the change in rainwater production at the intensity and temporal distribution levels, increasing the months of drought, while the levels of rainfall increase, concentrating in fewer months, basically in February and March. This is a situation that increases the water deficit especially when there is not enough infrastructure of hydraulic works for the storage and regulation of runoff.   Index Terms— Hydrology, rainfall, monthly distribution, annually distribution, climate change, El Niño phenomenon

Temporal and spatial characteristics of tonically active neurons of the primate's striatum

1995 ◽  
Vol 73 (3) ◽  
pp. 1234-1252 ◽  
Author(s):  
T. Aosaki ◽  
M. Kimura ◽  
A. M. Graybiel
Keyword(s):  
Light Emitting Diode ◽  
Temporal Analysis ◽  
Tonic Firing ◽  
Light Emitting ◽  
Macaque Monkeys ◽  
Tonically Active Neurons ◽  
The Mean ◽  
Temporal And Spatial Characteristics ◽  
Conditioning Stimuli ◽  
Visual Light

1. Tonically active neurons (TANs) in the primate striatum develop transient responses to sensory conditioning stimuli during behavioral training in classical conditioning tasks. In this study we examined the temporal characteristics of such TAN responses and mapped the sites of TANs responding to auditory and visual conditioned stimuli in the striatum in macaque monkeys. We further mapped the locations of TANs recorded acutely in the squirrel monkey striatum in relation to the neurochemically distinguished striosome and matrix compartments of the striatum, and made quantitative comparisons between the densities and compartmental distributions of TANs and those of four major types of striatal interneuron identified by histochemical and immunohistochemical staining. 2. We made recordings from 858 TANs at different sites in the striatum in two behaving macaque monkeys at different times during training with auditory (click) and visual (light-emitting diode flash) conditioning stimuli. TANs distributed across large parts of the striatum developed responses to the conditioning stimuli. The responses comprised a decrement of tonic firing (pause) followed by a rebound excitation. Measurements were made of the onsets, offsets, and durations of the pauses of individual TANs and of the interspike intervals (ISIs) of the same cells. 3. The mean duration of the pause responses (268.3 ms) was greater than the mean ISI of the same neurons (181 ms), suggesting that the pause represents an active suppression of TAN firing. The coefficient of variation (CV) for the pause responses was 0.28, compared with a CV of 0.63 for the same cells' ISIs. The population CV for the pauses was 0.16, compared with a population CV of 0.20 for the ISIs. These data, together with temporal analysis of the responses and population histograms, suggest that the pauses became temporally aligned across large parts of the striatum after learning. Analyses of variance (ANOVAs) were carried out to determine whether there were differences in the onset and offset latencies of the pause response or in the durations of the pause responses for TANs at different sites. These analyses suggested that, with rare exceptions, there was no difference in the timing of the TAN responses across large (> 10 mm3) parts of the striatum. 4. Comparisons of TAN responses in different regions of the striatum showed that, for responses to a given modality of conditioned stimulus, there were no significant differences in pause offset times for TANs recorded in the caudate nucleus or putamen, or for TANs recorded in more anterior or more posterior parts of these nuclei.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Characterizing Mathematics Learning in Colombian Higher Distance Education

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1740
Author(s):  
Elizabeth Martinez-Villarraga ◽  
Isabel Lopez-Cobo ◽  
David Becerra-Alonso ◽  
Francisco Fernández-Navarro
Keyword(s):  
Higher Education ◽  
Learning Strategies ◽  
Cultural Context ◽  
Mathematical Knowledge ◽  
Mixed Methods Research ◽  
Mathematics Learning ◽  
Sequential Design ◽  
Education Students ◽  
Approach To Learning ◽  
Conditional Knowledge

The aim of this work is to characterize the process of constructing mathematical knowledge by higher education students in a distance learning course. This was done as part of an algebra course within engineering degrees in a Colombian university. The study used a Transformative Sequential Design in mixed methods research. The analysis also determined the kinds of mathematical knowledge attained by the students and its relationship to the Colombian social and cultural context. The students acquired declarative, procedural, and conditional knowledge, while the learning strategies were often superficial. In a context where power is distant, students take on a passive approach to learning despite being highly respectful towards the educator. Thus, the educational system has the educator at the center.

scholarly journals To what extent emotion, cognition and behaviour enhance a student’s engagement: A case study on the MAJA teaching approach

2021 ◽  
pp. 147821032110320
Author(s):  
Matt M. Husain
Keyword(s):  
Higher Education ◽  
Cognitive Engagement ◽  
Learning Outcome ◽  
Soft Or ◽  
Final Exam ◽  
Course Content ◽  
Higher Education System ◽  
Student Aspirations ◽  
Class Environment

This empirical article problematises student engagement in today’s higher education system. The objective of this research is to stimulate a student’s behavioural, emotional and cognitive engagement. I employed an inclusive, inductive and reflexive approach and used mixed methods for collecting data from 948 volunteer participants. The preliminary findings illustrate that playing soft or lively music for a few minutes before a class as well as contextualising and delivering course content combined with enrolled students’ background, hobbies and preferences can go a long way in stimulating emotional and cognitive engagements. The findings also reveal that offering chair yoga during mid-term and/or final exam periods as well as encouraging students to hydrate can lead to increasing behavioural adjustments and then in attention and engagement. The results are encapsulated in a novel teaching framework, MAJA (meaning fun in Sanskrit) that stands for: (a) music, (b) anonymous class survey, (c) jest, and (d) aliment. The framework illuminates that when students tangibly sense a connection between a safe and comfortable class environment and course content, their participation increases and absenteeism decreases. They also promote student aspirations and accountability that facilitate critical thinking, an imperative learning outcome in higher education.

Artificial intelligence for decision making in higher education

2021 ◽  
pp. 1-2
Author(s):  
Carlos Enrique Montenegro Marin ◽  
Paulo Alonso Gaona Garcia ◽  
Edward Rolando Nuñez Valdez
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Decision Making
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