Academic Journal of Psychology and Counseling

Social Intelligence As A Predictor Of Competencies Among Prospective Counselors In Public Universities

Edith Omorionmwen Omogbai, Wellington Omosefe Jesuorobo — Mon, 29 Apr 2024 00:00:00 +0700

The study investigated social intelligence as a predictor of counseling competencies among prospective counselors in public universities in Edo and Delta States. Its aim was to precisely examine the level of social intelligence among these individuals and determine whether it predicts their counseling competencies. Survey research design using the correlational approach was implemented in the study. The population of the study comprised all Master’s students in public universities in Edo and Delta who had completed the practical counseling course. A sample of 81 prospective counselors was used for the study. The researchers used the Tromsꝋ Social Intelligence Scale (TSIS) and the Counselor Competency Scale (CCS) as research instruments. Data analyses were carried out using descriptive statistics (mean and standard deviation) and regression analysis. The findings of the study implied the social intelligence level of future counselors was high, and social intelligence significantly predicted counseling competencies of prospective counselors (F=8.021, p< 0.01, R2=0.09).

Influence of Personality Traits on Students’ Academic Achievement in Secondary Schools at Harari Regional State, Eastern Ethiopia

Moti Gelata, Gemechu Abera, Geleta Sitota — Mon, 29 Apr 2024 00:00:00 +0700

This study investigated the influence of personality traits on the academic achievement of the Secondary School at Harari Regional State, Eastern Ethiopia. The underachievement has assumed a worrisome dimension in the secondary school educational system. This study used the explanatory sequential mixed method design using a standardized instrument as a primary data-gathering tool. The study's respondents were four Secondary School students at Harari Regional State. The stratified random sampling technique was used to select 347 respondents from the randomly selected secondary schools in the study area. The findings of the study found that conscientiousness r(347) =0.46**, was highly statistically significantly positively related to academic achievement, whereas neuroticism r(347) =-0.39**) was highly statistically significantly negatively related to academic achievement. In this study, results from regression analysis showed that conscientiousness was the good and strongest individual contributor or predictor of academic achievement. In conclusion, personality traits significantly affect students’ academic achievement. It was recommended that teachers, parents, and students be educated on the knowledge that personality traits play a major role in how one can react to issues academic activities, and performance in school.

Cyber Crimes And Social Media Addictions: The Role Of Perceived Usage Of Conversational GPT-4 AI Model Among Residents In Nigeria

Caleb Onah, Chinelo Helen Ogwuche, Joy Oluwatoyin Oladejo — Mon, 03 Jun 2024 00:00:00 +0700

This study investigated cyber crimes and social media addictions: the role of perceived usage of conversational GPT-4 AI model among residents in Makurdi Nigeria. The cross-sectional survey design was used among 200 participants using the latest conversational GPT-4 AI model in their phones using the convenience sampling techniques. Hypothesis one results revealed there is a statistically significant between the usage of the conversational GPT-4 AI model and the incidence of cyber crime [R = .255, R2 = .065, [F (1,189) = 13.223, P< .01]. Hypothesis two showed that the baseline usage of the conversational GPT-4 AI model significantly predicts increase in social media addictions [R = .434, R2 = .188, [F (5,195) = 24.147, P<.01]. Hypothesis three revealed that the usage of conversational GPT-4 AI model is significantly associated with an increase in both cyber crime and social media addictions [R = .474, R2 = .226, [F (2,185) = 5.991; P<.01]. Based on this current study, there is need to develop and deliver educational programs aimed at informing residents and users about the responsible use of AI technologies, including those built on GPT-4 model.

From Conversation To Competence: Analysis Of The Influence Of Using ChatGPT And Learning Motivation In Increasing Self-Directed Learning

Tue, 25 Jun 2024 00:00:00 +0700

This study focuses on how ChatGPT and learning motivation affect students' self-directed learning (SDL). This research uses multiple regression analysis methods. The sampling technique used convenience sampling with 98 respondents who were undergraduate, master's, and doctoral students and had used ChatGPT for learning at least 1 (one) time. The research results show a significant and positive influence of ChatGPT and learning motivation on SDL, with a significance value of .00. The use of ChatGPT and learning motivation influence SDL by 75.7%. In comparison, the other 25% is influenced by other factors such as teacher influence, learning environment, metacognitive abilities, critical thinking abilities, and access to educational resources. If we look at the influence per variable, ChatGPT influences SDL by 31.2%, and Learning Motivation influences SDL by 44.3%. It can be concluded that Learning Motivation has a more significant influence on SDL than ChatGPT. These findings contribute new insights to the existing knowledge on the role of artificial intelligence and learning motivation in supporting student self-directed learning.