Papert Seymour popularized computational thought concept and emphasized its empowerment power, claiming that by giving offspring computers access, intelligent and a suitable simple language of programming, and peripheral devices able to produce on-line-real-time activity, we can offer them unparalleled power to carry out and innovate sensational ventures (Papert, 1980). Education of computational thinking in this vein, has the ability to change pupils from mere technology users to technology creators (Angeli, Fluck, Voogt, Cox, Webb, Zagami, & Malyn-Smith, 2016), allowing them to have a positive effect on people's lives and technical environment (Brennan & Resnick, 2012). Computational thinking education can help students develop their imagination (Voogt, Good, Fisser, Yadav, & Mishra 2015; Deschryver & Yadav, 2015), as well as inspire them to become technology producers through the development of programming objects (Angeli et al., 2016; Voogt, Good, Fisser, Yadav, & Mishra 2015).
According to the previous research, a good programming atmosphere will help students develop their creative self-efficacy (Burke, 2012). Thus, when students are more interested in an assignment, they are more confident in their ability to complete it, and they are more likely to begin working on it and finish it (Chiu & Klassen, 2010). Pupils who think they can finish a programming job successfully are likely more to become interested (Ntourou, Kalogiannakis, & Psycharis, 2021; Frymier et al., 1996). Additionally, effective approaches to impart computer programming frequently rise pupils' interest in programming (Wolz, Pearson, Stone, Switzer, & Pulimood, 2011; Denner, Werner, Campe, & Ortiz, 2014). Students who are interested in programming or who have a good attitude toward teamwork may have more programming empowerment. Hidi (2006), defines programming interest as a psychological condition in which an individual exhibits positive feelings, concentration, greater focus, or a long-term relatively proclivity to programming actions. A pupil who is more interested in a domain like programming than others sees it as more than just a way to achieving positive outcomes. Instead, students are intrigued by it and investigate it in order to learn more about its implications and effects (Ryan & Deci, 2017, self-determination theory). Furthermore, such a pupil has a greater internal locus of causality than other pupils (Dimmock, Magaraggia, Jackson, & Podlog, 2013).
As a result, students perceive the job more easily (Gattiker, 1992), are eager to spend more time on it (Ryan & Deci, 2017), have higher self-efficacy in programming (Venkatesh & Venkatesh, 2000), and grow greater competency in it (Venkatesh & Speier, 2000).When faced with task difficulties or challenges, such a student is more likely than others to see it as a challenge, persist in finding innovative solutions, and underestimate the drawbacks (Senko & Harackiewicz, 2005; Ryan & Deci, 2017). As a result, computer science and information technology courses offer students the chance to improve the computational thinking skills they will need to function in today’s society, which is highly dependent on computation. Information Technology and College Computer Science introductory courses have a high attrition rate and are generally considered to be challenging (Watson & Li, 2014; Robins, Rountree, & Rountree, 2003). In recent years, as interest in making coding available to every college student has increased, a growing number of young individuals are joining college courses with some programming background and programming language familiarity (Lye & Koh, 2014), which could help to increase computer science and information technology persistence rates.
Aside from the growing programming utility and analytical thought in our daily lives, information technology and computer science are likewise a rapidly growing and high-paying sector in which, traditionally, the availability of properly trained employees has failed to keep up with demand. As stated by the Bureau of Labor Statistics (2014), through 2022, eight of the ten jobs in the information technology and computer fields are projected to rise at a rate greater than eleven percent. Despite this rapid growth, it is well known that females continue to be underrepresented in the profession, with the gender gap between men and women entering the field widening. Consistent with the Taulbee study of Computing Association Research from 2013–2014, nearly 86 percent of bachelor's degree recipients in the United States in computer science in 2014 were men. Though computer science bachelor's degrees’ reported number increased by fourteen percent in 2014 from 2013, women's proportion earning computer science degrees decreased during that period (Zweben & Bizrot 2015). Recently, the number of students offering computer science and information technology has increased over the last decade (Cuny, 2012). However, in Ghanaian senior high schools, students are rarely exposed to programming and also lack meaningful learning opportunities. As a result, the study sought to examine college students’ interest in programming at Kwame Nkrumah University of Science and Technology (KNUST).
Statement of problem
Regardless of age, a novice programmer encounters several hitches while trying to study concepts of programming. For instance, selection structures, variables, recursion, loop structures, pointers, arrays, parameters, references, input/output/handling, structured data types, using language libraries, and error handling (Lahtinen et al. 2005). Computer programming carries young kids into interaction with basic concepts of programming in a suitable developmentally manner, with stress on young users’ skills and needs. In Ghanaian universities, students find it difficult to learn computer programming. This has resulted in a loss of interest in learning computer programming. Empirically, several studies have been done on students’ interest in programming in developing and developed countries (Ntourou et al., 2021; Papadakis, Kalogiannakis, & Zaranis, 2016; Papadakis, 2016; Kanaki & Kalogiannakis, 2018) but very limited in Africa. Currently, there are limited studies on the effect of age on college students’ interest in programming. To bridge the gap in literature, the study sought to investigate college students’ interest in programming with age and gender as a factor.
The following questions was addressed in the study;
- What is college students’ interest in programming?
- Does gender has effect on college students’ interest in programming?
- Does age have an effect on college students’ interest in programming?
Embedding computational thinking in science courses
The computational nature of current science necessitates the incorporation of computational thinking into science textbooks. As said by Weintrop et al. (2016), incorporating computational tools and techniques into science classes allows students to gain a more realistic understanding of the content of scientific areas, as well as better prepare them for appropriate career pathways. From a pedagogical standpoint, the deliberate application of computational tools and competencies can help students better understand science subject (Wilensky et al. 2014; Sengupta et al. 2013). The converse is also true; science classes give a valuable background and a diverse set of problems to which computational thinking can be applied (Wilensky et al. 2014; Jona et al. 2014). As said by Weintrop et al. (2016), this viewpoint contrasts noticeably from isolating the teaching of computational thinking in a separate course, where, in most cases, real-world problems and applications are not represented in the assignments students are given. According to Blikstein (2013), the motivation for diversified and purposeful involvement in computational and scientific courses is most likely established if the themes of the assignments are realistic and pertinent to the actual world. As a result, as said by Weintrop et al. (2016), we advocate for an educational method that includes computational programming in science contexts.
According to Kurkovsky (2007), when CS is compared to other academic subjects, students feel it to be much more difficult. As said by Malan and Leitner (2007), it's considered a "nerdy" and "not a cool course to take". Learning a program is seen as a difficult task. Many new programmers have difficulty learning programming principles and using such concepts in code writing, according to data. As said by Roy et al. (2012), the syntactic subtleties of a language, as well as the computational ideas, are difficult for novice programmers to grasp. Furthermore, according to Guzdial (2004), they have difficulties with basic algorithmic structures like loops, conditions, and the creation of programs using them. Moreover, for decades, enterprise-level languages have been used to introduce programming like C, Java, and C++ in high schools and universities. Programming is a subject that students study at school that aims to equip students with skills and knowledge (Papadakis & Kalogiannakis, 2019). Writing a computer program is a progressive "hands-on activity" for learners to secure an essential skill in their programming career. For instance, students need to gain proficiency with the essential punctuation and then the semantics, structure, and style step by step. During lesson delivery, the instructor will not hold up learners to completely understand programming (Ntourou et al., 2021). Writing computer programs is not just a matter of varying levels of expertise, but additionally, different aptitudes. Writing computer programs is a procedure that starts with interpreting an algorithm into program code. The difficult part is to decipher the required specification into an algorithm. A good algorithm delivers the correct program. Along these lines, students are expected to be talented regarding every procedure: structuring the algorithm, interpreting the algorithm into program language, and composing the programming language with the right punctuation (Kanaki & Kalogiannakis, 2018).
Programming as a course is offered from semester by a semester at the university. Mostly, the first semester for new students, second and third semester for those who have completed the first semester (Papadakis, 2016). Learners who do not perform in the assessment must quit the subject anyway. Also, individuals above the expected mark will continue to the subsequent class. Lamentably, certain students even though they breezed through the assessment, however, they develop no confidence in programming. At the point when they take the next course, they will confront an issue where they have to gain proficiency with another thing just as enhancing their coding ability. The language programming used in indicating a programming introductory course likewise is an issue (Papadakis & Kalogiannakis, 2019). Programming class is to show the student the most proficient method to program. Students accept that writing computer programs is a challenging thing to learn to have a good grade. But we cannot anticipate that students should be talented in programming just within 14 weeks. Anyway, it can take somebody 10 years to be a gifted software engineer (Rahmat et al., 2012).
College Students’ Interest in Programming
An individual’s sentiment whose attention, concern, or interest is especially connected by something. The individual has an incredible enthusiasm for the verse of Donne. Something that worries, includes, draws the attention of, or excites the interest of an individual. These inclinations are theory and chess (Rico et al., 2011). A study on pedagogy adapted to create interest in pupils offering a programming course by Venugopal-wairagade (2016). With versatile application improvement getting one of the most looked for after decisions by software engineering students, designers and organizations, a teacher training a seminar on the equivalent to a bunch of fledglings ought to guarantee that the most ideal instructing learning systems are received to create enthusiasm among learners in the study room (Fresko & Alhija, 2015). The creator utilized a mixed methodology comprising of customary, m-learning and e-learning systems. These thusly, comprised of different instructing and assessment techniques (Kamenez, Smirnova, Vaganova, Bystrova, & Tsarapkina, 2019). Through this paper, the creator examines the effect of the strategies embraced as a major aspect of the analysis, on students’ enthusiasm and their particular execution. The example comprised of twenty-two postgraduate software engineering pupils. Their reactions to the managed instruments, their learning materials and scores (LMS that includes laptops and projectors) get to logs were broke down.
The creator had the option to accomplish factually huge outcomes concerning the students' advantage and their presentation, for the most part, two methodologies coordination of LMS, and showing the points by building up an application in different stages all through the length of the course. It was discovered that concerning venture work, persistent association with the teacher was an ideal and acknowledged methodology by the pupils. The research additionally uncovered the misinterpretations that a teacher might have while teaching computer programming (Papadakis, 2016). The outcome of this investigation might be utilized by educators showing any computer programming language in advanced education. Toward the finish of the research, it was discovered that pupils, all in all, comprehend following coding rules’ significance once composing a program, and it has no association with their programming ability.
It was likewise discovered that once utilizing laptops in class by the student may, to a little degree, rely upon the convenience of the laptop (Kamenez et al., 2019). The investigation likewise uncovered that the students’ excitement need not demonstrate that they are enthused about getting their work assessed consistently (or week after week). In any case, it was seen that the normal reaction to the inquiry in regards to week by week entries and assessments was 1.45, which shows that the majority of the students that shaped the example favour week by week groups instead of presenting the work toward the finish of the semester with no week after week collaboration (Fresko & Alhija, 2015). One reason for this could be that they need to stay away from the very late problem and this causes them to take a shot at their venture normally in a progressively productive way. It was additionally discovered that once coordinating e-learning in the teaching method, if a pupil is effectively occupied with LMS utilization, it might prompt their insight in specific parts of the course, for this situation, creating Android applications (Ntourou et al., 2021).
As the connection between the two factors is frail to direct, we can say that LMS usage might aid in producing the course enthusiasm. A significant perception that was made throughout the research was that there exists a solid positive connection between pupils' marks and their reaction to stage shrewd realizing once instructing programming (Papadakis, Kalogiannakis, & Zaranis, 2016). This demonstrates if the educator encourages a programming course utilizing a couple of uses and builds up the application by circulating the advancement of the highlights all through the semester (Papadakis & Kalogiannakis, 2019). The students might have the option to take a gander at the ideas from a more extensive view and might have the option to relate the ideas with each other since all the ideas are constituents of one entire framework. This might be a superior methodology than showing one idea and afterwards showing another idea, with no connection between the two. The consequences of this investigation might be utilized by educators learning computer programming or any technology building course.
According to Witherspoon et al. (2016), students' programming experience is linked to major variations in motivation to seek added opportunities of programming. In other words, pupils who perceived themselves as being extra actively associated with programming were likely more to be motivated to seek added experiences of programming. These findings are in line with those of further active studies learning, which show that teaching that explicitly includes pupils in the process of learning will enhance pupil attitudes toward learning (Casad & Jawaharlal 2012; Alemdar & Rosen 2011; Smith et al. 2014; Prince 2004). It also backs up arguments that cultivating a sense of self as a "programmer" will encourage pupils to seek added opportunities of programming (Worsley & Blikstein 2012; Barton & Tan 2010). The current research discovered that there were no substantial variations in motivation to follow programming between pupils who collaboratively programmed and those who programmed independently. This seems to be at odds with research that suggests that in robotics contexts, teamwork can boost student motivation (Mitnik et al. 2008; Eguchi 2015).
Age and programming interest
Demographics have also been related to empowerment in previous studies. Mature pupils frequently see subjects in school as less important and believe they are less capable than younger students. Older students face more decontextualized teaching than younger pupils, which several find less useful or important in their lives every day. Consequently, they frequently regard subjects in school as less significant (Lepper, Iyengar, & Corpus, 2005). Also, as pupils grow older, they grow into extra mindful of their relative and peers capabilities (Dweck, 2000), motivation achievement, general school-related attitudes, and lowering their domain-specific attitudes (Chiu & Klassen, 2010). Instead of an objective decline in skill or performance, mature pupils' perceived competency might decline because of uncertainties coming from less instruction personalized and improved educational pressures perceptions (Pajares & Cheong, 2003). As a result, mature pupils are likely to regard computer programming as less competent and less meaningful than younger students.
Gender and programming empowerment
Boys are more interested in programming computers than children, owing in part to common media assumptions. Male computer specialists are portrayed in the mass media as both girls’ anti-role models and boys’ role models, inspiring boys to pursue programming computers while uninspiring girls (Master, Meltzoff, & Cheryan, 2016). Classroom children with computer science stereotypical objects (video games, Star Trek posters) displayed less interest in the subject than classroom children without those objects (Cheryan, Steele, Davies, & Plaut, 2009). As a result, we anticipate that boys will be more interested in programming computers than girls. Boys are interested more than girls are in programming.
Physical Computing and Computational Experiment
Physical computing is said to be useful to people of all ages because it gives a high level of learning, encourages engagement, interest, and sharing of ideas, fosters constructive and creative learning, and cultivates creativity and imagination (Przybylla & Romeike, 2014; Fokides & Papoutsi, 2020). However, the goals to be attained as well as the Physical Computing learning environment must be carefully chosen, since it may be both enjoyable and challenging. It involves extremely taxing tasks that increase cognitive load and may result in a dissatisfying learning experience (Jin, Kearns, & Haynie, 2016). The concept of computational experiment is included in this context, where modeling and computers replace the traditional experimental set-up and simulation replaces the traditional experiment (Zacharia & Michael, 2016; Zacharia, 2007; Psycharis, 2011). It is particularly intriguing because it refers to real issue solving and stimulates students to produce predictions and hypotheses that support the growth of scientific process. It mixes Physics, Math, and the theory of information (Psycharis, 2011).
We may confidently presume that it aids in the development of critical thinking skills and a good attitude toward science (Psycharis et al., 2014; Psycharis, 2013). Many scientists propose using computer experimentation when there is no laboratory available and the experiment is unsafe or needs complex and time-consuming processes (Zacharia, 2007). These types of experiments are significantly easier to employ in the classroom because they need less space and time, do not disturb the classroom's normal operation, and can be repeated much more readily than traditional experiments, giving students more experience (Zacharia, 2007; Klahr et al., 2007). However, Klahr et al. (2007) highlighted that natural materials should be used in regions where the senses are required or where contact with the real world is required. To summarize, the ultimate goal of teaching programming should be to maximize the effectiveness of the learning process by utilizing the potential of both experimental methods; it is therefore advisable to combine computational experiment with classical experiment when teaching programming, as the two are complementary (Zacharia & Michael, 2016; Zacharia, 2007; Jaakkola & Nurmi, 2008).