How Students Can Get Better Grades – Cognitive Skills Influencing Academic Performance

Abstract

Knowing the skills/factors that affect academic performance, we could intervene and students could realise the components influencing higher academic success. Intelligence is the capacity to solve problems by thinking, being posited as a general ability that accounts for the co-variation of many specific abilities. Both nonverbal and verbal intelligence are determined by a combination of innate capacities and acquired skills/knowledge. Attention appears to be a ubiquitous feature in perceptual experience, being plausibly a feature of cognition as well. Visual memory encompasses memory representations that maintain data about the perceptual properties of viewed stimuli, while auditory memory involves the retention of auditory information to allow time for comprehension to occur. The purpose of our research is to explore and identify cognitive skills that significantly influence academic performance (the grades/marks obtained by the students). The participants were 2^nd year students at the Faculty of Physical Education and Sports within the National University of Physical Education and Sports of Bucharest, aged between 19 and 22 years. The instruments used to explore the cognitive abilities of the students were: the Prague Distributive Attention Test, the Visual Short-Term Memory Test, the Rey Auditory Test and Abstract Reasoning Test. To verify the degree of association between variables, the Sommer’s d-indicator was used. The results underline significant positive associations between the results for short-term auditory memory, nonverbal intelligence and the academic performance of the students .

Keywords: Academic performanceattentionvisual memoryauditory memorynonverbal intelligence

Introduction

Over time, researchers have tried to highlight the skills/factors that affect academic performance. Knowing these, we could intervene and students could realize the components influencing higher academic results. Starting from this idea, our study investigates mental abilities that may condition higher academic success.

Intelligence is the capacity to solve problems by thinking, being posited as a general ability that accounts for the covariation of many specific abilities (Sternberg & Kaufman, 2011). Horn and Cattel (1966) discuss about fluid and crystallized intelligence. Fluid intelligence describes capacities that are innate and not dependent of on experience or prior education. Crystallized intelligence describes abilities that rely on skills, knowledge acquired from experience. Traditionally, the tests considered to measure fluid intelligence are nonverbal, while tests traditionally considered to measure crystallized intelligence are verbal. But it seems that “fluid” and “crystallized” are not very good labels for the two commonly types of tests (verbal and nonverbal). Johnson and Bouchard (2007) and Johnson et al. (2007) assert that nonverbal intelligence cannot be entirely fluid (independent of experience), because it may be improved by training and because it is influenced by environmental factors in studies of heritability. Also, verbal intelligence cannot be entirely dependent on experience (crystallized), because it is genetically influenced - it is just as heritable as nonverbal intelligence. Thus, both nonverbal and verbal intelligence are determined by a combination of innate capacities and acquired skills/knowledge. As Kaufman (2013) mentioned, “it is incorrect to assume that tests of nonverbal fluid reasoning are somehow measuring intelligence in its purest form, completely divorced from experience and culture” (p. 192). Likewise, a vocabulary test or a general knowledge test often requires inference and deduction, involving fluid reasoning skills - influenced both by genes and culture (which are always interacting with each other). However, as the author argues, fluid reasoning involves inferring underlying patterns based on minimal data, whereas tasks encompassing a well-organized knowledge base place fewer demands on fluid reasoning.

Attention appears to be a ubiquitous feature in perceptual experience, being plausibly a feature of cognition as well (Wu, 2011). Through attention, a person performs an important selection of the stimuli. A student in class, for example, can select specific items among many items, objects, features or the contents of various possible thoughts. Attention is necessary to get things done, accompanying mental activity, appearing as a background condition, helping us to serve action - both bodily and mental behaviours (reasoning, imagining, thinking etc.). Horghidan, Mitrache and Tüdös (2001) argue that, through attention, mental energy can be focused on an internal/external event (sensory event or psychological event). Attention can be divided into three kinds: selective, distributive and sustained attention (Sun, Hu, & Liu, 2014). Distributive attention involves two or more arousals in the individual. In these conditions, for completing complex tasks, attention will be assigned to different activities. In class, students may have difficulties in maintaining and switching attention, in performing efficient complex tasks involving multiple simultaneous decisions. In the field of sport, it has been found that attention represents a good predictor for the decision time (Grigore, Predoiu, & Păunescu, 2015). In order to obtain better results (as a student) when evaluating attention and, as a consequence, maybe better results at school, practicing team sports is very important (Grigore, Mitrache, Predoiu, & Păunescu, 2013). Also, we mention Tüdös, Predoiu and Predoiu (2015) and Grigore, Predoiu, Predoiu and Mitrache (2016) who emphasize that, for better performance in sports competitions (and in academic competition, which is not too different in terms of mental abilities, involving intelligence, willpower, logical thinking, creativity, perseverance, self-confidence etc.), it becomes essential, in the preparation process, to perform tasks demanding attention.

Visual memory encompasses memory representations that maintain data about the perceptual properties of viewed stimuli, but the format in which the information is encoded can vary from low-level imagistic representations to higher-level visual representations (Luck, & Hollingworth, 2008). Visual memory can be subdivided into visual sensory memory, visual short-term memory (VSTM) and visual long-term memory (VLTM). Authors mention that visual short-term memory and visual working memory are typically used to refer to the same memory system and VSTM is highly robust over changes position (Phillips, 1974). VSTM maintains visual information from objects, schemes for many seconds, and the consolidation of data (into VSTM) is dependent on attention. It seems that VSTM representations provide the starting point for building VLTM representations. Regarding auditory memory, it involves the retention of auditory information to allow time for comprehension to occur. This retention of auditory data is referred to as “short-term auditory memory” (Mense, Debney, & Druce, 2006). Authors have found that children with short-term auditory memory difficulties may: seem distracted, appear to daydream, say “What?” a lot, be unresponsive to verbal instruction or became frustrated. Rowe and Rowe (2007) assert that difficulties (in the case of children) in the area of learning, attention, social skills or behaviour (after assessments made by psychologists, paediatricians, audiologists) are caused by the difficulties experienced with auditory processing or short-term auditory memory.

Problem Statement

There is no doubt that identifying the mental factors that affect academic performance is a relevant research theme. Shoukat et al. (2013) have found that student’s marks (as a dependent variable) depend on the father’s/ guardian’s social economic status, student’s age and daily study hours. Along with these three factors highlighted, researchers also investigated the gender, residential area, accommodation trend, tuition, faculty of study and schooling environment (as independent variables). But only the income, age and study time significantly correlated with student’s performance. Thus, the income level of parents has a positive effect upon the test score recorded by the students, in the case of Islamia University. Other researchers (Considine & Zappala, 2002) achieved similar results in Australia - parents’ social status positively influences student’s academic performance. Regarding age, the results underlined a negative correlation, while the strongest connection observed was between the academic success and study hours (study time) - considered as the most important factor influencing the student’s academic performance. Other studies rely on the facilities offered by the school. It was argued (Crosnoe, Johnson, & Elder, 2004) that the existing resources/facilities in school play an important role, positively influencing the academic performance of the students. But which are the mental factors that condition academic performance? We know, based on common sense, that the following are important to obtain good grades: intelligence, memory, attention, conscientiousness, emotional control, perseverance, mental strength, motivation, willpower, observation, logical thinking, creativity, self-confidence etc. But, again, are some mental abilities significantly associated with high academic success? The present research investigates this aspect, more exactly, studies the importance of nonverbal (fluid) intelligence, the importance of visual and auditory memory and of distributive attention.

Research Questions

Given the complexity of the domain, including diverse influences of socio-demographic variables, the present study asks if there are any significant associations between the results for distributive attention, nonverbal intelligence, visual short-term memory, short-term auditory memory and the academic performance of the students. Thus, the hypothesis we want to test is H1: There are significant associations between the performances obtained by the students for cognitive skills (nonverbal intelligence, visual short-term memory, short-term auditory memory, distributive attention) and the academic performance (the overall average of grades/marks).

Purpose of the Study

The purpose of our research is to explore and identify cognitive skills that significantly influence academic performance (the grades/marks obtained by the students).

Research Methods

Findings

In the preliminary data analysis, we investigated the possibility of the existence of extreme values for the results obtained by the students in the four tests (perhaps because of fatigue or low interest). The box-plot charts showed no outliers.

To verify the degree of association between variables (results in the four tests and grades/marks obtained by the students), the Sommer’s d-indicator was used. We have chosen this statistical indicator because of the asymmetric relationships between variables: the academic performance (the overall average of grades/marks) is considered to be the dependent variable, while the performance obtained by the students in the four tests represents the independent variable.

Conclusion

The study demonstrates a significant positive association between cognitive skills and academic performance. More precisely, there is a significant positive association between the results for short-term auditory memory and the academic success of the students. High scores in the case of short-term auditory memory are related to better academic performance, students obtaining better general scores. This can be explained by the fact that students with good auditory memory remember information that has been presented orally and recall data that they have read to themselves (even silent reading involves a form of listening). As Cusimano (2001) said, it is important, for a good recall of the information, to pay attention and listen to our silent input of words. Tan (1999) argues that difficulties in the case of short-term auditory memory can impact on the social and academic development and can lead to frustration and diminished self-esteem. Knowing these, we must help students develop strategies to efficiently remember auditory information. First, students must listen actively: they need to have an alert posture, reduce excessive movements, look at the speaker, think about what the speaker is saying and ignore the background noise (students must think about how they listen - a metacognitive task). Next, students can use visualisation (making an internal visual image of what they have heard). Also, representations should not be limited to visual aspects, but may include what a person hears or feels (Predoiu, 2016). In addition, students can use rehearsal - repetition of the keywords, linking ideas and chunking (information is broken down into smaller parts that are easier to retain).

Through our research, we have also emphasised that there is a significant positive association between the performance for nonverbal intelligence (mostly fluid, innate) and the marks recorded by the students at the end of the first year of studies. Thus, high scores for nonverbal intelligence are related to better academic performance. Knowing that nonverbal intelligence is not entirely innate (independent of experience), students can be stimulated through specific training/programs, which enhance this type of intelligence.

We specify that in the case of visual short-term memory and distributive attention, no significant association with academic performance (the grades/marks recorded by the students) has been found. In addition to the revealed data, in order to improve the academic success of the students, we must underline the importance of teacher’s expectations. The literature (Pânişoară, & Pânişoară, 2005) asserts that teacher’s expectations are causes of student performance. If teachers have low performance expectations from their students, this leads to poor academic results of the students. The limits of our study are the cultural differences and the age of participants - we are aware that the findings could be different in another setting. Also, the testing period was not similar, the students being tested in the morning or in the afternoon and not the same day (they were investigated from Monday to Thursday, according to the moment they were at school).

Further research is necessary to reveal the effects of different mental and psychophysical skills upon academic performance. It is also important to study (besides nonverbal or fluid intelligence, visual short-term memory, short-term auditory memory and distributive attention), creativity, verbal intelligence, analogical reasoning abilities, personality traits (autonomy, anxiety, self-confidence, aggression, conscientiousness or sensation seeking) and psychomotricity (for example, speed and distance estimation, reaction time, conditional abilities such as endurance, speed, strength, coordination abilities such as coordination, balance, spatial orientation), considering that the participants are students at the Faculty of Physical Education and Sports.

References

• Considine, G., & Zappala, G. (2002). Influence of social and economic disadvantage in the academic performance of school students in Australia. Journal of Sociology, 38, 129-148.
• Crosnoe, R., Johnson, M. K., & Elder, G. H. (2004). School size and the interpersonal side of education: An examination of race/ethnicity and organizational context. Social Science Quarterly, 85(5), 1259-1274.
• Cusimano, A. (2001). Learning Disabilities: There is a cure. A guide for parents, educators and physicians. Pennsylvania, US: Achieve Publications.
• Denscombe, M. (2014). The good research guide: For small-scale social research projects. London, UK: Open University Press.
• Grigore, V., Mitrache, G., Predoiu, R., & Păunescu, M. (2013). Use of computer technology in evaluating the concentration and mobility of attention. Central and Eastern European Online Library, 3, 137-142.
• Grigore, V., Predoiu, R., & Păunescu, M. (2015). The role of the computer technology in the development of attention and decision time – A regression model. CEEOL, 3, 254-259.
• Grigore, V., Predoiu, A., Predoiu, R., & Mitrache, G. (2016). Cognitive and psychomotor dimensions and the sport performance in the case of junior women handball players. Discobolul – Physical Education, Sport and Kinetotherapy Journal, 11, 128-134.
• Horghidan, V., Mitrache, G., & Tüdös, Şt. (2001). Psihologie normală şi patologică. Bucureşti: Globus.
• Horn, J. L., & Cattel, R. B. (1966). Refinement and test of the theory of the fluid and crystallized general intelligences. Journal of Educational Psychology, 57, 253-270.
• Johnson, W. & Bouchard, T. J. Jr. (2007). Sex differences in mental abilities: G masks the dimensions on which they lie. Intelligence, 35, 23-39.
• Johnson, W., Bouchard, T. J. Jr., McGue, N., Segal, N. L., Tellegen, A., Keyes, M., & Gottesman, I. I. (2007). Genetic and environmental influences on the Verbal-Perceptual-Image Rotation (VPR) model of the structure of the mental abilities in the Minnesota study of twins reared apart. Intelligence, 35, 542-562.
• Kaufman, S. B. (2013). Ungifted: Intelligence redefined. New York, NY: Basic Books.
• Luck, S. J., & Hollingworth A. (2008). Visual memory. Oxford, UK: Oxford University Press.
• Mense, B., Debney, S., & Druce, T. (2006). Ready, set, remember: Short-term auditory memory activities. Melbourne: ACER Press.
• Oprea, V., Niţu, E. L., Chiriacescu, D., & Lungu, E. P. (2003). Procese psihice. Probe de limbaj. In E. Vrăsmaş & V. Oprea (Ed.), Set de instrumente, probe, teste pentru evaluarea educaţională a copiilor cu dizabilităţi (pp. 75-108). Bucureşti: MarLink.
• Pânişoară, G., & Pânişoară, I. O. (2005). Motivarea eficientă. Iaşi: Polirom.
• Phillips, W. A. (1974). On the distinction between sensory storage and short-term visual memory. Perception & Psychophysics, 16, 283-290.
• Predoiu, R. (2016). Psihologia sportului. Maximizarea performanţei sportive. Iaşi: Polirom.
• Rowe, K. S., & Rowe, K. J. (2007). ‘Literacy behaviour’ and auditory processing: Building ‘fences’ at the top of the cliff in preference to ‘ambulance services’ at the bottom. 12th CHERI Conference (pp. 34-52). Sydney, 5-6 September.
• Shoukat, A., Haider, Z., Munir, F., Khan, H., & Ahmed, A. (2013). Factors contributing to the students’ academic performance: A case study of Islamia University sub-campus. American Journal of Educational Research, 1(8), 283-289.
• Sternberg, R. J., & Kaufman, S. B. (2011). The Cambridge handbook of intelligence. Cambridge, UK: Cambridge University Press.
• Sun, F., Hu, D., & Liu, H. (2014). Foundations and practical applications of cognitive systems and information processing. New York, NY: Springer.
• Tan, L. (1999). Auditory processing at school no. 3. Huntington Beach, CA: Listening Works.
• Tüdös, Șt., Predoiu, R., & Predoiu, A. (2015). Topographical memory and the concentration of attention in top female tennis players. Social and Behavioural Sciences, 190, 293-298.
• Wu, W. (2011). Attention as selection for action. In C. M. Mole, D. Smithies & W. Wu (Eds.), Attention: Philosophical and psychological essay (pp. 97-117). Oxford, UK: Oxford University Press.