ASSESSMENT OF INTELLIGENCE CONFERENCE


Assessment of Intelligence Conference is one of the leading research topics in the international research conference domain. Assessment of Intelligence is a conference track under the Psychology Conference which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Psychology.

internationalconference.net provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of (Psychology).

Assessment of Intelligence is not just a call for academic papers on the topic; it can also include a conference, event, symposium, scientific meeting, academic, or workshop.

You are welcome to SUBMIT your research paper or manuscript to Assessment of Intelligence Conference Track will be held at “Psychology Conference in San Francisco, United States in November 2021” - “Psychology Conference in Istanbul, Turkey in November 2021” - “Psychology Conference in Singapore, Singapore in November 2021” - “Psychology Conference in Bangkok, Thailand in December 2021” - “Psychology Conference in Paris, France in December 2021” .

Assessment of Intelligence is also a leading research topic on Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, Elsevier, Scopus, Web of Science.

XXIX. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 02 - 03, 2021
SAN FRANCISCO, UNITED STATES

XXX. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 12 - 13, 2021
ISTANBUL, TURKEY

XXXI. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 19 - 20, 2021
SINGAPORE, SINGAPORE

XXXII. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 15 - 16, 2021
BANGKOK, THAILAND

XXXIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 28 - 29, 2021
PARIS, FRANCE

FINISHED

I. INTERNATIONAL PSYCHOLOGY CONFERENCE

MARCH 19 - 20, 2019
ISTANBUL, TURKEY

FINISHED

II. INTERNATIONAL PSYCHOLOGY CONFERENCE

JUNE 26 - 27, 2019
PARIS, FRANCE

FINISHED

III. INTERNATIONAL PSYCHOLOGY CONFERENCE

AUGUST 21 - 22, 2019
LONDON, UNITED KINGDOM

FINISHED

IV. INTERNATIONAL PSYCHOLOGY CONFERENCE

OCTOBER 08 - 09, 2019
NEW YORK, UNITED STATES

FINISHED

V. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 12 - 13, 2019
ROME, ITALY

FINISHED

VI. INTERNATIONAL PSYCHOLOGY CONFERENCE

FEBRUARY 13 - 14, 2020
LONDON, UNITED KINGDOM

FINISHED

VII. INTERNATIONAL PSYCHOLOGY CONFERENCE

APRIL 15 - 16, 2020
BARCELONA, SPAIN

FINISHED

VIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

MAY 11 - 12, 2020
ISTANBUL, TURKEY

FINISHED

IX. INTERNATIONAL PSYCHOLOGY CONFERENCE

JUNE 05 - 06, 2020
SAN FRANCISCO, UNITED STATES

FINISHED

X. INTERNATIONAL PSYCHOLOGY CONFERENCE

JULY 20 - 21, 2020
PARIS, FRANCE

FINISHED

XI. INTERNATIONAL PSYCHOLOGY CONFERENCE

AUGUST 10 - 11, 2020
NEW YORK, UNITED STATES

FINISHED

XII. INTERNATIONAL PSYCHOLOGY CONFERENCE

SEPTEMBER 10 - 11, 2020
TOKYO, JAPAN

FINISHED

XIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

SEPTEMBER 16 - 17, 2020
ZÜRICH, SWITZERLAND

FINISHED

XIV. INTERNATIONAL PSYCHOLOGY CONFERENCE

OCTOBER 21 - 22, 2020
BARCELONA, SPAIN

FINISHED

XV. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 02 - 03, 2020
SAN FRANCISCO, UNITED STATES

FINISHED

XVI. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 12 - 13, 2020
ISTANBUL, TURKEY

FINISHED

XVII. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 19 - 20, 2020
SINGAPORE, SINGAPORE

FINISHED

XVIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 15 - 16, 2020
BANGKOK, THAILAND

FINISHED

XIX. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 28 - 29, 2020
PARIS, FRANCE

FINISHED

XX. INTERNATIONAL PSYCHOLOGY CONFERENCE

FEBRUARY 13 - 14, 2021
LONDON, UNITED KINGDOM

FINISHED

XXI. INTERNATIONAL PSYCHOLOGY CONFERENCE

APRIL 15 - 16, 2021
BARCELONA, SPAIN

FINISHED

XXII. INTERNATIONAL PSYCHOLOGY CONFERENCE

MAY 11 - 12, 2021
ISTANBUL, TURKEY

FINISHED

XXIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

JUNE 05 - 06, 2021
SAN FRANCISCO, UNITED STATES

FINISHED

XXIV. INTERNATIONAL PSYCHOLOGY CONFERENCE

JULY 20 - 21, 2021
PARIS, FRANCE

FINISHED

XXV. INTERNATIONAL PSYCHOLOGY CONFERENCE

AUGUST 10 - 11, 2021
NEW YORK, UNITED STATES

FINISHED

XXVI. INTERNATIONAL PSYCHOLOGY CONFERENCE

SEPTEMBER 10 - 11, 2021
TOKYO, JAPAN

FINISHED

XXVII. INTERNATIONAL PSYCHOLOGY CONFERENCE

SEPTEMBER 16 - 17, 2021
ZÜRICH, SWITZERLAND

FINISHED

XXVIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

OCTOBER 21 - 22, 2021
BARCELONA, SPAIN

Psychology Conference Call For Papers are listed below:

Previously Published Papers on "Assessment of Intelligence Conference"

  • Assessing and Evaluating the Course Outcomes of Control Systems Course Mapping Complex Engineering Problem Solving Issues and Associated Knowledge Profiles with the Program Outcomes
    Authors: Muhibul Haque Bhuyan, Keywords: Complex engineering problem, knowledge profiles, OBE, control systems course, COs, PIs, POs, assessment rubrics. DOI:10.5281/zenodo. Abstract: In the current context, the engineering program educators need to think about how to develop the concepts and complex engineering problem-solving skills through various complex engineering activities by the undergraduate engineering students in various engineering courses. But most of them are facing challenges to assess and evaluate these skills of their students. In this study, detailed assessment and evaluation methods for the undergraduate Electrical and Electronic Engineering (EEE) program are stated using the Outcome-Based Education (OBE) approach. For this purpose, a final year course titled control systems has been selected. The assessment and evaluation approach, course contents, course objectives, course outcomes (COs), and their mapping to the program outcomes (POs) with complex engineering problems and activities via the knowledge profiles, performance indicators, rubrics of assessment, CO and PO attainment data, and other statistics, are reported for a student-cohort of control systems course registered by the students of BSc in EEE program in Spring 2021 Semester at the EEE Department of Southeast University (SEU). It is found that the target benchmark was achieved by the students of that course. Several recommendations for the continuous quality improvement (CQI) process are also provided.
  • Guidelines for Developing, Supervising, Assessing and Evaluating Capstone Design Project of BSc in Electrical and Electronic Engineering Program
    Authors: Muhibul Haque Bhuyan, Keywords: Course outcome, capstone design project, assessment and evaluation, electrical and electronic engineering. DOI:10.5281/zenodo. Abstract: Inclusion of any design project in an undergraduate electrical and electronic engineering curriculum and producing creative ideas in the final year capstone design projects have received numerous comments at the Board of Accreditation for Engineering and Technical Education (BAETE) several times by the mentors and visiting program evaluator team members at different public and private universities in Bangladesh. To eradicate this deficiency which is needed for getting the program accreditation, a thorough change was required in the Department of Electrical and Electronic Engineering (EEE) for its BSc in EEE program at Southeast University, Dhaka, Bangladesh. We suggested making changes in the course curriculum titles and contents, emphasizing to include capstone design projects, question setting, examining students through other standard methods, selecting and retaining Outcome-Based Education (OBE)-oriented engineering faculty members, improving laboratories through purchasing new equipment and software as well as developing new experiments for each laboratory courses, and engaging the students to practical designs in various courses and final year projects. This paper reports on capstone design project course objectives, course outcomes, mapping with the program outcomes, cognitive domain of learning, assessment schemes, guidelines, suggestions and recommendations for supervision processes, assessment strategy, and rubric setting, etc. It is expected that this will substantially improve the capstone design projects offering, supervision, and assessment in the undergraduate EEE program to fulfill the arduous requirements of BAETE accreditation based on OBE.
  • Assessing and Evaluating the Course Outcomes of Electrical Circuit Course for Bachelor of Science in Electrical and Electronic Engineering Program
    Authors: Muhibul Haque Bhuyan, Sher Shermin Azmiri Khan, Keywords: OBE, COs, POs, assessment and evaluation, electrical circuit course. DOI:10.5281/zenodo. Abstract: At present, it is an imperative and stimulating task to grow the concepts and skills of undergraduate students in any course. Educators must build up students' higher-order complex and critical thinking abilities. But many of them find it difficult to assess and evaluate these abilities of students who undertake their courses during undergraduate studies. In this research work, a simple assessment and evaluation process for the electrical circuit course of the undergraduate Electrical and Electronic Engineering (EEE) program is reported using the Outcome-Based Education (OBE) approach. The methodology of the work, course contents design, course outcomes (COs) preparation and mapping it with program outcomes (POs), question setting following Bloom's taxonomy, assessment strategy of the students, CO and PO evaluation records, statistics, and charts have been reported for a student-cohort of electrical circuit course taken in Spring 2019 Semester at EEE Department of Southeast University (SEU). It is found that the benchmark fixed by the course instructor has been achieved by the students of that course through CO assessment and evaluation. Recommendations of the course teacher for further quality enhancement based on CO achievement are also presented.
  • Conceptualizing Thoughtful Intelligence for Sustainable Decision Making
    Authors: Musarrat Jabeen, Keywords: Thoughtful intelligence, Sustainable decision making, Thoughtful decision support system. DOI:10.5281/zenodo. Abstract: Thoughtful intelligence offers a sustainable position to enhance the influence of decision-makers. Thoughtful Intelligence implies the understanding to realize the impact of one’s thoughts, words and actions on the survival, dignity and development of the individuals, groups and nations. Thoughtful intelligence has received minimal consideration in the area of Decision Support Systems, with an end goal to evaluate the quantity of knowledge and its viability. This pattern degraded the imbibed contribution of thoughtful intelligence required for sustainable decision making. Given the concern, this paper concentrates on the question: How to present a model of Thoughtful Decision Support System (TDSS)? The aim of this paper is to appreciate the concepts of thoughtful intelligence and insinuate a Decision Support System based on thoughtful intelligence. Thoughtful intelligence includes three dynamic competencies: i) Realization about long term impacts of decisions that are made in a specific time and space, ii) A great sense of taking actions, iii) Intense interconnectivity with people and nature and; seven associate competencies, of Righteousness, Purposefulness, Understanding, Contemplation, Sincerity, Mindfulness, and Nurturing. The study utilizes two methods: Focused group discussion to count prevailing Decision Support Systems; 70% results of focus group discussions found six decision support systems and the positive inexistence of thoughtful intelligence among decision support systems regarding sustainable decision making. Delphi focused on defining thoughtful intelligence to model (TDSS). 65% results helped to conceptualize (definition and description) of thoughtful intelligence. TDSS is offered here as an addition in the decision making literature. The clients are top leaders.
  • Machine Learning Techniques in Bank Credit Analysis
    Authors: Fernanda M. Assef, Maria Teresinha A. Steiner, Keywords: Artificial Neural Networks, ANNs, classifier algorithms, credit risk assessment, logistic regression, machine learning, support vector machines. DOI:10.5281/zenodo. Abstract: The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.
  • A Robust Optimization Method for Service Quality Improvement in Health Care Systems under Budget Uncertainty
    Authors: H. Ashrafi, S. Ebrahimi, H. Kamalzadeh, Keywords: Service quality assessment, healthcare resource allocation, robust optimization, budget uncertainty. DOI:10.5281/zenodo. Abstract: With the development of business competition, it is important for healthcare providers to improve their service qualities. In order to improve service quality of a clinic, four important dimensions are defined: tangibles, responsiveness, empathy, and reliability. Moreover, there are several service stages in hospitals such as financial screening and examination. One of the most challenging limitations for improving service quality is budget which impressively affects the service quality. In this paper, we present an approach to address budget uncertainty and provide guidelines for service resource allocation. In this paper, a service quality improvement approach is proposed which can be adopted to multistage service processes to improve service quality, while controlling the costs. A multi-objective function based on the importance of each area and dimension is defined to link operational variables to service quality dimensions. The results demonstrate that our approach is not ultra-conservative and it shows the actual condition very well. Moreover, it is shown that different strategies can affect the number of employees in different stages.
  • Music Aptitude and School Readiness in Indonesian Children
    Authors: Diella Gracia Martauli, Keywords: Bracken school readiness assessment, music aptitude, primary measures of music audiation, school readiness. DOI:10.5281/zenodo. Abstract: This study investigated the relationship between music aptitude and school readiness in Indonesian children. Music aptitude is described as children’s music potential, whereas school readiness is defined as a condition in which a child is deemed ready to enter the formal education system. This study presents a hypothesis that music aptitude is correlated with school readiness. This is a correlational research study of 17 children aged 5-6 years old (M = 6.10, SD = 0.33) who were enrolled in a kindergarten school in Jakarta, Indonesia. Music aptitude scores were obtained from Primary Measures of Music Audiation, whereas School readiness scores were obtained from Bracken School Readiness Assessment Third Edition. The analysis of the data was performed using Pearson Correlation. The result found no correlation between music aptitude and school readiness (r = 0.196, p = 0.452). Discussions regarding the results, perspective from the measures and cultures are presented. Further study is recommended to establish links between music aptitude and school readiness.
  • Personal Factors and Career Adaptability in a Call Centre Work Environment: The Mediating Effects of Professional Efficacy
    Authors: Nisha Harry, Keywords: Call centre, professional efficacy, career adaptability, emotional intelligence. DOI:10.5281/zenodo. Abstract: The study discussed in this article sought to assess whether a sense of professional efficacy mediates the relationship between personal factors and career adaptability. A quantitative cross-sectional survey approach was followed. A non–probability sample of (N = 409) of which predominantly early career and permanently employed black females in call centres in Africa participated in this study. In order to assess personal factors, the participants completed sense of meaningfulness and emotional intelligence measures. Measures of professional efficacy and career adaptability were also completed. The results of the mediational analysis revealed that professional efficacy significantly mediates the meaningfulness (sense of coherence) and career adaptability relationship, but not the emotional intelligence–career adaptability relationship. Call centre agents with professional efficacy are likely to be more work engaged as a result of their sense of meaningfulness and emotional intelligence.
  • Predicting the Success of Bank Telemarketing Using Artificial Neural Network
    Authors: Mokrane Selma, Keywords: Bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network. DOI:10.5281/zenodo. Abstract: The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.
  • Virtual Reality Learning Environment in Embryology Education
    Authors: Salsabeel F. M. Alfalah, Jannat F. Falah, Nadia Muhaidat, Amjad Hudaib, Diana Koshebye, Sawsan AlHourani, Keywords: Virtual reality, student assessment, medical education, 3D, embryology. DOI:10.5281/zenodo.3593206 Abstract: Educational technology is changing the way how students engage and interact with learning materials. This improved the learning process amongst various subjects. Virtual Reality (VR) applications are considered one of the evolving methods that have contributed to enhancing medical education. This paper utilizes VR to provide a solution to improve the delivery of the subject of Embryology to medical students, and facilitate the teaching process by providing a useful aid to lecturers, whilst proving the effectiveness of this new technology in this particular area. After evaluating the current teaching methods and identifying students ‘needs, a VR system was designed that demonstrates in an interactive fashion the development of the human embryo from fertilization to week ten of intrauterine development. This system aims to overcome some of the problems faced by the students’ in the current educational methods, and to increase the efficacy of the learning process.