scholarly journals Flow, Achievement Level, and Inquiry-Based Learning

2018 ◽  
Vol 30 (1) ◽  
pp. 74-106 ◽  
Author(s):  
Lindsay A. Borovay ◽  
Bruce M. Shore ◽  
Christina Caccese ◽  
Ethan Yang ◽  
Olivia (Liv) Hua
Keyword(s):  
Exploratory Study ◽  
Cognitive Outcomes ◽  
Achievement Level ◽  
Inquiry Instruction ◽  
Affective Outcomes ◽  
Inquiry Based Learning ◽  
High Achieving

Beyond cognitive outcomes, inquiry instruction can have positive general and differentiated affective outcomes. In this exploratory study, teacher-nominated high- to low-average achievers in Grades 5 through 9 ( N = 272, mean age 11.7 years), in classrooms exhibiting rare, occasional, and frequent inquiry qualities, were assessed on Csikszentmihalyi’s construct of flow, following a recent unit and reflecting on their favorite subject. We focused on flow because it addresses education and life in general, and flow and inquiry invoke challenge and persistence. Interviews complemented these data. High-achieving participants reported most flow in inquiry and in their favorite subjects; in both situations, they could participate in determining the content. All students reported greater flow in inquiry-based activities and environments, and in their favorite subjects versus recent units. All preferred challenging over easy work although for different reasons. All highlighted feeling able to succeed and interest in an activity to experience flow.

Design and Develop a Cybersecurity Education Framework Using Capture the Flag (CTF)

2019 ◽  
pp. 123-153 ◽  
Author(s):  
Li Jing Khoo
Keyword(s):  
Exploratory Study ◽  
Information Technologies ◽  
National Level ◽  
Tertiary Level ◽  
Achievement Level ◽  
Cyber Threats ◽  
Skill Gaps ◽  
Computer Knowledge ◽  
Malaysian Students ◽  
The Relationship

The rise of cyber threats is projecting the growth of cybersecurity education. Malaysian students who are interested in studying computing and information technologies suffer from knowledge and skill gaps because the earliest exposure of formal computer knowledge happens only at tertiary level education. In addition, the ever-evolving cyber landscape complicated the gaps and exposure. This chapter reveals the learner's motivation factor through an exploratory study in a national level cybersecurity competition. By simulating a real-world cyber landscape, a customized cybersecurity game, Capture the Flag was designed, developed, and validated as an experiment to study the relationship between learners' motivation and achievement level.

scholarly journals Investigation of Affective and Socioeconomic Variables Predicting the Achievement Level of Low- and High-Achieving Students

2019 ◽  
Vol 5 (1) ◽  
pp. 209
Author(s):  
Ercan Çoban ◽  
Ömer Kamış
Keyword(s):  
Test Anxiety ◽  
Achievement Motivation ◽  
Self Efficacy ◽  
Epistemological Beliefs ◽  
Environmental Awareness ◽  
Binary Logistic Regression ◽  
Achievement Level ◽  
Socioeconomic Variables ◽  
High Achieving Students ◽  
High Achieving

This study aimed to determine the affective and socioeconomic variables significantly predicting achievement level of low- and high-achieving students. The data of 1323 low-achieving and 2022 high-achieving Turkish students participated in the PISA 2015 were used in the study. The data were analyzed by using binary logistic regression. The findings showed that test anxiety; achievement motivation; enjoyment of cooperation; environmental awareness; environmental optimism; science self-efficacy; epistemological beliefs; economic, cultural and social status index (ESCS), and the information and communication technology (ICT) resources index were significant predictors of the achievement level of low- and high-achieving students. While test anxiety and environmental optimism scores of low- achieving students were higher, achievement motivation, enjoyment of cooperation, environmental awareness, science self-efficacy, epistemological beliefs, ESCS, and ICT resources scores were higher among high-achieving students. 

Use of the Mmpi Underachievement Scale as an Aid in Counseling Academic Low Achievers in College

1973 ◽  
Vol 32 (1) ◽  
pp. 151-157 ◽  
Author(s):  
Gary S. Felton
Keyword(s):  
College Students ◽  
Academic Achievement ◽  
Early Detection ◽  
Low Achievers ◽  
High Achievers ◽  
Low Achievement ◽  
Achievement Level ◽  
High Achieving ◽  
College Dropouts

47 high-achieving college students and 47 college dropouts were compared on the 24-item MMPI Underachievement Scale. The high achievers' mean score of 8.00 differed significantly ( p < .001) from the low achievers' mean score of 13.44. Probabilities of academic achievement level and score on the Underachievement Scale suggest that the scale may be useful in early detection of academic low achievement.

A Comparison of the Effects of Logo and a CAI Learning Environment on Skills Acquisition

1987 ◽  
Vol 3 (4) ◽  
pp. 461-477 ◽  
Author(s):  
Joan K. Gallini
Keyword(s):  
Cognitive Outcomes ◽  
Skills Acquisition ◽  
Group Discussions ◽  
Affective Outcomes ◽  
Treatment Groups ◽  
Hands On ◽  
Fourth Grade Students ◽  
Programming Techniques ◽  
Computer Based ◽  
The Impact

The present study investigated the impact of computer-based environments in enhancing a particular set of cognitive outcomes. Of specific focus was a comparison between a Logo and a more traditional CAI context in promoting one's ability to follow directions and construct directions in the process of solving problems. Forty-four fourth-grade students were randomly assigned to one of the two treatment groups. Subjects engaged in group discussions and hands-on computer activities over a five-week period. In the Logo group subjects essentially tested programming techniques in constructing a variety of structures. The CAI group worked with similar stimuli, but in a “program-directed” format. Results demonstrated higher posttest achievement in the Logo group's ability to formulate directions in different instances. However, the following direction performances were essentially the same for both groups. The study raises important theoretical issues regarding the role of specific types of features of computer-based environments in effecting different types of cognitive as well as affective outcomes. Of particular note are the merits of such research to generate new hypotheses about CBI contexts adapted to meet individual differences in learning.

Patterns of Interaction in Family Triads with High-Achieving and Low-Achieving Children

1976 ◽  
Vol 39 (3_suppl) ◽  
pp. 1291-1299 ◽  
Author(s):  
Patricia Krige
Keyword(s):  
Family Process ◽  
Achievement Level ◽  
Interactional Pattern ◽  
Parental Pair ◽  
The Family ◽  
The Mean ◽  
High Achieving ◽  
Patterns Of Interaction

The patterns of interaction between the parents and the child in family triads of high-achieving and low-achieving boys and girls and their parents were compared. Forty family triads were studied. The mean age of the children was 12 yr., 1 mo. Fathers of boys and girls did not differ in over-all dominance in the family process. Parents shared dominance but fathers of boys differed from fathers of girls in how this dominance was applied. Fathers' interactional pattern with their wives was flexible, influenced by the sex and achievement level of the children. These factors influenced fathers' interaction with their children and also mothers' interaction with their husbands. Mothers' behaviour toward their children was influenced by sex but much less so by achievement level. The sex of the child significantly influenced his behaviour toward his mother but the achievement level not to the same extent. In essence, the interaction of the parental pair with their children seemed to be the important factor in achievement.

Learner-Controlled Computing: A Description and Rationale

1975 ◽  
Vol 3 (3) ◽  
pp. 207-216 ◽  
Author(s):  
Stuart D. Milner
Keyword(s):  
Problem Solving ◽  
Learner Control ◽  
Thinking Skills ◽  
Cognitive Outcomes ◽  
Affective Outcomes ◽  
Self Confidence ◽  
Use Of Technology ◽  
Drill And Practice ◽  
It Controlling ◽  
Specific Learning

This paper discusses a use of technology in which the student controls the computer (e.g., computer programming) instead of it controlling the student (e.g., drill-and-practice). A description of the nature of this mode of computer use is provided, and some examples are given. A rationale for learner control is discussed in terms of cognitive and affective outcomes of computing. The cognitive outcomes include relatively specific learning and thinking skills and more general systematic methods of problem solving. Affective outcomes include self-confidence, curiosity and exploratory behaviors, and motivation.

scholarly journals Excessive Boredom Among Adolescents: A Comparison Between Low and High Achievers

2020 ◽  
Author(s):  
Manuel M. Schwartze ◽  
Anne C. Frenzel ◽  
Thomas Goetz ◽  
Anton Karl Georg Marx ◽  
Corinna Reck ◽  
...  
Keyword(s):  
Personality Traits ◽  
Self Report ◽  
High Achievers ◽  
Personality Profiles ◽  
Achievement Level ◽  
School Students ◽  
Expressive Suppression ◽  
Social And Emotional ◽  
High Achieving Students ◽  
High Achieving

Existing research shows that high scholastic boredom is correlated with a range of undesirable behaviors and personality traits and that the main antecedents of boredom are being over- or under-challenged. No study to date, though, seems to have systematically compared students who are highly bored and low-achieving (thus, likely over-challenged) with students who are highly bored and high-achieving (thus, likely under-challenged). Hence, merely knowing that students are highly bored might be insufficient for drawing conclusions about students’ behavior and personality, without taking their achievement level into account. We, therefore, investigated if low- versus high-achieving students who experience strong mathematics boredom show different behaviors and personality traits. The sample consisted of 1,404 German secondary school students (fifth to 10th grade, mean age 12.83 years, 52% female). We used self-report instruments to assess boredom in mathematics, behavior (social and emotional problems, positive/negative affect, emotion regulation), and personality traits (neuroticism and conscientiousness). In comparing highly bored students (more than one SD above M, n = 258) who were low versus high achievers (as indicated by the math grade, n = 125 / n = 119), results showed that there were no mean level differences across those groups for the behavior and personality trait constructs, with only three exceptions: conduct problems and expressive suppression (higher for low achievers) and positive affect (higher for high achievers). In conclusion, our results suggest that high boredom can occur in both low and high achieving students and that bored low- and high-achievers show largely similar behaviors and personality profiles.

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