Gender Gap in Computer Science: Preferences and Performance

Transcription

1 Aricle Gender Gap in Compuer Science: Preferences and Ioannis Berdousis a, Maria Kordaki b * a: Compuer Engineer, Universiy of he Aegean, Deparmen of Culural Technology and Communicaions Universiy Hill, Myilene, Greece i.berdousis@aegean.gr Tel: Fax: b: Universiy of he Aegean, Deparmen of Culural Technology and Communicaions Universiy Hill, Myilene, Greece m.kordaki@aegean.gr Tel: Fax: *: corresponding auhor Absrac: The aim of he presen sudy is o invesigae boh he performance and preferences of males and females Compuer Science (CS) graduaes. In order o aain he above goal, a quaniaive case sudy was conduced regarding 89 degrees, acquired from 2006 o 2012, from he Deparmen of Compuer Science and Technology, Universiy of Peloponnese, Greece. The analysis of he daa revealed ha in erms of performance, no significan differences beween he mean s of males and females exis, in almos mos of he courses included in he curriculum of he aforemenioned CS deparmen. Any saisically significan differences in performances were presen in almos equal number of courses in favor of males and females. I seems also, ha females performed beer in he courses hey seleced more han males. Regarding preferences, in CS courses, i seems ha gender differences are exisen. Males preferred more han females did core programming courses and advanced opics of Sofware Sysems, compuer neworks, compuer engineering, roboics and mahemaics, whereas females preferred more he sudy of algorihms and securiy issues, compuer fracals, daa managemen, compuer archiecure, and mobile communicaion. In addiion, females preferred courses in reference wih humaniies and social sciences, CS erminology, and career opporuniies. Ye, females did no selec any of programming lab-based courses, compuer engineering, compuer nework issues and roboics. Keywords: Compuer Science; Teriary Educaion; Course Selecion; ; Gender Gap 1. Inroducion Women are underrepresened in mos of he Science, Technology, Engineering and Mah (STEM) fields as well as in Compuer Science (CS) (Cohoon and Aspray 2006; Hill e al. 2010; Camp 2012; Ascraf e al. 2012). Acually, CS remains an especially heavily male-dominaed field, even afer several years of exensive effors o promoe female paricipaion (Camp 2012). The raio of women o men 2017 by he auhor(s). Disribued under a Creaive Commons CC BY license.

2 2 of involved in CS shrinks dramaically from early suden years o working years. In fac, women are underrepresened in all fields of CS educaion; eaching saff in secondary educaion (Kordaki and Berdousis 2015), undergraduae and graduae sudies (Kordaki and Berdousis 2017) as well as in he academic secor (Camp 2002; Hill e al. 2010; Berdousis and Kordaki 2016). This phenomenon, acknowledged as 'he pipeline shrinkage problem' is complex and muli-faced, bu well known and documened (Gu rer and Camp 2002; Ascraf e al. 2012). Over ime, research has idenified several key social and srucural facors affecing women s paricipaion in CS, ofen deerring hem from choosing fuure educaion or careers in CS, revealing ha he reasons for such low paricipaion are mulilayered (Gürer and Camp 2002; Margolis and Fisher 2003; Cohoon and Aspray 2006; Barker and Aspray 2006; Ascraf e al. 2012). Firs, Gürer and Camp (2002) defined 14 such facors, while a laer review from Ascraf e al revealed ha females percepions, ineres, confidence and aiudes owards CS are shaped by he larger environmen hey learn abou CT including: compuing experience, suppor, sereoypes, and educaion. In ha sense, girls lose ineres in CS early on, as hey don' gain as much experience wih compuers as boys do (Margolis and Fisher 2003), while he kind of he compuing experience seems o be a crucial facor (Barker and Aspray 2006). Wha is more, parens and family members have significan influence as role models wih he ypes of messages or beliefs hey communicae o girls boh implicily and explicily (Ashcraf e al. 2012), which in some cases, maybe uninenionally, can be obsacles for he female members (Gürer and Camp 2002). Mos recen sudies argue ha one novel and powerful social facor ha may perpeuae he underrepresenaion of women in CS is he sereoypes abou he culure of he field, which in some cases ac as educaional gaekeepers, discouraging females from enering CS (Cheryan e al. 2009; Cheryan e al. 2015). In some cases, sudens have sereoypes abou he culure of CS and girls face negaive sereoypes abou heir abiliies, making hem feel like hey do no belong in CS. Key facors ha discourage females paricipaion in CS, conribuing o he loss of ineres of females, are conneced o he educaion as well, and especially, he CS curriculum, he eaching pracices and he uncomforable for females learning environmens (Ashcraf e al. 2012). However, can gender gap in CS be aribued o differences in performance and in CS course preferences? Such quesions have been addressed in oher disciplines in STEM educaion bu sill remain unanswered in CS. As suppored in he lieraure review, acual gender differences in cogniive skills and academic abiliy are non-exisen. However, individuals sill believe in and behave in response o he belief of such gender differences (Alkhadrawi 2015). As a resul, a large gender dispariy persiss in higher educaion and careers in he STEM fields in which male paricipaion and success in hese fields exceeds ha of females (Alkhadrawi 2015). Acually, any gender differences are neiher biological nor cogniive bu hey are socially consruced myhs ha consiue obsacles ha hinder female success. These myhs are no real in he scienific and empirical sense regarding acual measures of abiliy and inelligence, bu hey are real because hey have real social implicaions. In fac, evidence in he STEM field indicae ha i seems o be no significan differences in performance beween males and females, wih males o perform slighly beer on he consruc of science and have more self-efficacy (Hyde e al. 1990; Jacobs e al. 2002; Ding 2006; Kiran and Sungur 2012). The fac ha he gender gap in measures of STEM abiliy and achievemens has narrowed and nearly disappeared has been menioned since 90 (Mickelson 1989; Adelman 1991; Meece and Courney 1992). The abiliy and inelligence of males and females in science subjecs showed lile o no difference (Mickelson 1989) while, especially in mah performance gender differences were small, and in some cases females ouperformed males, bu only by a negligible amoun (Hyde e al. 1990). Laer sudies emphasized on he performance of males and females in STEM in high school, and specifically, on he ools ha school uses o measure science achievemens: s and es scores. The resuls regarding he gender differences beween s and es scores are ineresing. While males and females are similar in achievemen, females have higher final s in STEM while males have higher es scores (Saunders e al. 2004; Briner 2008; Sanrock 2008). Briner (2008) found ha females in life science class earned higher s han boys, while Saunders e al. (2004) found ha females mah final s were significanly higher han males. By conras, in mos cases males perform beer on science ess (Ormrod 2007). Neverheless, here is evidence supporing ha females perform as

3 3 of well as males in academic achievemen, including science (Mickelson 1989; O'Reilly and McNamara 2007), and acually, female and male sudens do no differ significanly on he objecive examinaion of achievemen in science knowledge (Freedman 2002). Neverheless, in a review of 25 years of evidence, Jacobs (2005) argued ha differences in s is generally weak and concluded ha females have achieved increasing success in STEM courses, closing he gender gap, while a laer sudy showed ha no significan gender differences were found on five science academic oucomes (Mahews e al. 2009). Acually, research suggess ha he domain-specific self-compeence beliefs and domain-specific moivaion and performance is he key o he performance, as hose sudens who believe ha hey have he abiliy o accomplish a paricular ask perform beer and are more moivaed o selec increasingly challenging asks (Jacobs e al. 2002). Thus, when differen domains are aken ino consideraion, females perform beer han males on he social aspecs of science facors and males end o perform beer han females on he consrucs of science facors (Kiran and Sungur 2012). Anoher sudy in high school suppors ha, gender gaps in he percenage of graduaes earning credis in specific STEM courses vary by course (Laird e al 2009). A larger percenage of female han male graduaes earned credis in biology, chemisry, and healh science/echnology, while, on he oher hand a larger percenage of males han females earned credis in physics, engineering, engineering/science echnologies, and CS (Laird e al. 2009). Likewise, a mos recen sudy suppored ha, a higher percenage of male han female high school graduaes expressed ineres in mahemaics, and he same was rue for ineres in science (Cunningham e al. 2015). Neverheless, Van de Gaer e al. (2008) conended ha gender differences in mah paricipaion and in mah achievemen can be shifed over ime. A heir sudy hey noiced ha, while a firs males scored significanly higher han females, he gap evenually closed and females surpassed males a higher levels. In ha sense, i seems ha inervenions in he curriculum in order o adap i o he ineress of females, promoing heir abiliies (Haussler and Hoffmann 2002), as well as providing exracurricular and informal learning experiences, such as paricipaion in science compeiions or science-relaed field rips (Cunningham 2007) can endorse females science performance and ineres. Despie he fac ha, i seems ha here is no significan difference in he performance of males and females in STEM courses, a closer examinaion of he course selecions reveals cerain persisen differences in preferences regarding STEM. Even if some evidence suggess ha males and females do no differ significanly in he numbers in STEM courses, and ha he gap beween females and males in he acual number of mahemaics and science courses aken, appear o be diminishing (Alkhadrawi 2015), ye, gender differences remained in he kinds of courses chosen. Sudies over he pas years revealed ha gender gaps persis in erms of enrollmen in specific courses and majors. Even when he overall number of males and females in science majors is nearly equal, he specific field wihin science sill differs significanly: males ake high-level mahemaics, engineering, CS, and physical sciences in higher numbers, while more females ake biology and chemisry (Kenway and Gough 1998; Bussey and Bandura 1999; Coley, 2001; Amelink 2009). According o he Amelink (2009) males are more likely o major in mahemaics and quaniaively oriened sciences. On he oher hand, research daa argue ha in high school, females acually ake biology and chemisry more han males do (Amelink 2009). I seems ha males aach a higher value and uiliy o mah and have higher self-concep in mah, reasoning why hey choose o paricipae more in mah han females (Van de Gaer e al. 2008). Evidence from college reveals differences in he preferences as well. Marion (1993) argued ha nearly as many females as males ook science and mah courses, while male sudens enrolled in he more mahemaically and quaniaively demanding STEM courses. In addiion o choices made in courses and majors, choices made for aciviies ouside of school also appear o differ. Some evidence suggess ha females were less likely han males o paricipae in science aciviies ouside he classes (Amelink, 2009). This lower level of paricipaion may affec science ineress and fuure paricipaion in science fields. The differences in course preferences are refleced in career choices as well. Upon closer inspecion wihin he science and mah fields, differences emerge in erms of which field wihin STEM, males and females pursue in heir educaion and careers (Amelink, 2009).

4 4 of Despie he relevan research in STEM fields, a sudy invesigaing gender differences wihin CS in erms of performance and course preferences in higher educaion has no been repored. In his sense, he research quesions of he curren research are he following: 1. Wha are he differences beween males and females course preferences in CS eriary educaion, and 2. Wha is he performance of males and females in courses of CS deparmens This sudy could conribue o he field of CS curriculum and insrucion by deermining o wha exen more effor is needed in he educaion sysem o dispel gender myhs and remove perceived boundaries wihin cerain CS career pahs. Subsequenly, his sudy could lead o he incorporaion of eaching sraegies o challenge persisen myhs -abou gender differences in CS performance- and perceived obsacles abou gender and CS. The paper is organized as follows: Nex, he conex of he sudy is presened and hen, he resuls of he daa analysis. A subsaniaed discussion and inerpreaion of he research findings is followed, and conclusions are drawn. Finally, he limiaions of he sudy and fuure research dimensions are idenified. 2. Conex of he sudy This sudy focuses on he invesigaion of: (a) he gender differences in course preferences in CS, and (b) he relaionship beween gender and performance in CS courses. For his reason, 89 degrees covering a 6-year period of graduaion a he Deparmen of Compuer Science and Technology (DCS&T), Universiy of Peloponnese, Greece, were sudied. In fac, his sudy has aken ino consideraion he degrees of all graduae sudens who enrolled from 2002 o The number of male graduaes was 69 (N1=69; percenage 77,53%) and he number of female graduaes was 20 (N2=20; percenage 22,47%). These daa are in-line wih a relevan research abou a represenaive ypical percenage of CS graduaes from CS Deparmens in Greece (Kordaki and Berdousis 2017). According o he curriculum of he Deparmen, in his specific academic period, sudens had o enroll and successfully be examined in 21 compulsory courses as well as in 25 elecives in order o receive he degree. To his end, he s of he graduaes of he period under sudy, in boh compulsory courses and elecives were sudied and quaniaively-analyzed. In DCS&T, he courses are classified ino 3 divisions, namely: Theoreical Compuer Science (TCS), Sofware Sysems (SS), Compuer Technology and Compuer Sysems (CTCS). TCS division conains 3 compulsory courses and 11 elecives; SS division encloses 8 compulsory courses and 29 elecives; while CTCS includes 3 compulsory courses and 15 elecives. In addiion, for each division Mah and Physics (M&P) consising of 7 courses were compulsory while sudens were also obligaed o selec courses from 21 General Educaion (GE) elecives. The procedure followed is described below. The daa regarding he 89 graduaes were colleced from he official records of DCS&T wihou any reference o he personal daa of he graduaes apar from heir gender. Those daa referred o he gender of each graduae, he courses ha she/he had enrolled and successfully examined along wih her/his s. Then, a saisical analysis (descripive and inferenial) was realized in erms of: (a) preferences of males and females in each of he elecive courses; he percenage of graduaes who seleced each course were esimaed, and (b) performance of males and females in each of he compulsory/elecive courses; mean and sandard deviaion values were calculaed and independen sample -ess were conduced o compare he mean s of male and female graduaes. In erms of mehodology, his sudy can be characerized as a case sudy (Cohen e al. 2013). The resuls of he daa analysis are presened in he nex secion. 3. Resuls In his secion, he resuls emerged from he daa analysis are presened ino subsecions for each of he above-menioned 3 divisions as well as for M&P compulsory courses and GE elecives. For each one of he aforemenioned group of courses, performance (in compulsory courses) as well as preferences and performance in elecives are presened in Tables. Specifically, he Tables referring o he performance in compulsory courses presens descripive saisics - mean s and sandard

5 5 of deviaion () values - along wih he independen samples es resuls for he equaliy of means. As far as he elecives are concerns, similar Tables are generaed regarding graduaes performance, while for graduaes preferences wo more columns are added o presen he percenage of graduaes (males and females) who seleced he corresponding elecive. In each of he divisions, graduaes preferences and performance in elecives are spli ino wo Tables (a and b), he firs of which presens he elecives ha were seleced by a higher percenage of male compared o female graduaes, while he second presens he elecives ha were seleced by a higher percenage of female compared o male graduaes. All Tables are sored in a descending order of he mean difference of he s Graduaes Choices and in Theoreical Compuer Science courses TCS Compulsory courses: Graduaes performance Table 1 illusraes ha male graduaes achieved higher s in Inroducion o he Science & Technology of Informaics and Compuaional Science courses compared o females. On he oher hand, females performed slighly beer in Theory of Compuaion. Neverheless, he differences in he mean s are no saisically significan. Table 1. in Theoreical Compuer Science compulsory courses Graduaes performance in Theoreical Compuer Science compulsory courses Group Saisics Independen Samples Tes - Male Female T es for equaliy of means Grade (J) Inroducion o he Science & Technology of Informaics Compuaional Science Ι Theory of Compuaion TCS elecives: Graduaes preferences As i is shown in Table 2a, 4 ou of he 10 available elecives of he TCS division were chosen more by males. The seleced applied mahemaics and heoreical CS courses ( Operaional Research, and Combinaional Opimizaion ), he sudy of mahemaical srucures ( Graph Theory ) and oher advanced opics ( Advanced Topics in TCS ). On he oher hand, Table 2b presens ha females seleced more elecives (6 elecives) from he TCS division a a higher percenage compared o males. Females preferred more han males he sudy of algorihms ( Compuaional Geomery, Compuaional Complexiy, Parallel algorihms ), he pracice and sudy of echniques for secure communicaion ( Crypography ), and compuer fracals. In addiion, i is worh noing ha Compuaional Science II was seleced from he half of female sudens (50%) and almos half of he male sudens (49,28%), while Operaional Research was seleced from jus one female suden.

6 6 of Table 2a. Preferences and performance in Theoreical Compuer Science elecives: : courses seleced more by males Graduaes preferences and performance in Theoreical Compuer Science elecives Preferences Group Saisics Male Female Male Female Independen Samples Tes - T es for equaliy of means graduaes who seleced he course (%) Sig difference Advanced Topics in TCS Combinaorial Opimizaion Operaional Research Graph Theory * *The difference is significan a he 0.05 level TCS elecives: Graduaes performance Concerning he performance of male graduaes in hese 10 elecives of he TCS division, Tables 2a and 2b reveals ha hey performed beer in jus 2 courses compared o females. Acually, hey performed beer in jus 1 ou of he 4 elecives hey seleced a a higher percenage compared o females. Insead, female graduaes performed beer in 5 ou of he 6 elecives hey chose more compared o males (Table 2b) and in 8 overall (Tables 2a and 2b). The only female who chose Operaional research performed excellen ( 10 ), while in Compuaional Science II, a popular choice for boh males and females, he mean s were excepionally high. Overall, male graduaes performed excellen -mean higher han 8,5- in 3 TCS elecives: Advanced Topics in Theoreical CS, Compuaional Science ΙΙ and Operaional Research, while females performed excellen in he same 3 TCS elecives plus Graph Theory. Noneheless, he independen sample -es ha was conduced o compare he mean s of male and female graduaes indicaed ha, acually, here was a saisically significan difference in he mean of Graph Theory for males (M=6.18; =1.53) and females [M=9.25; =0.35; (11)=-2.716, p=0.02] Table 2b. Preferences and performance in Theoreical Compuer Science elecives: courses seleced more by females Graduaes preferences and performance in Theoreical Compuer Science elecives Preferences Group Saisics Male Female Male Female Independen Samples Tes - T es for equaliy of means graduaes who seleced he course (%) (J) (J) Sig difference Compuaional Geomery Compuaional Science ΙΙ Parallel Algorihms Compuaional Complexiy Fracals Crypography

7 7 of Sudens Choices and in Sysem Sofware (SS) courses SS compulsory courses: Graduaes Regarding he compulsory courses of he SS division, Table 3 reveals ha male graduaes performed beer in 6 ou of he 8 courses. Noneheless, he saisical analysis reveals ha he only difference ha is saisical significan difference is in he mean of Compuer Programming I for males (M=7.31; =1.62) and females [M=6.15; =0.99; (51.509) =3.964, p<0.0001]. Females performed beer in 2 compulsory courses wih he difference in he mean s of Human Compuer Ineracion ( difference 0.60 in favor of females) o be saisically significan [(87)=-1.869; p=0.045]. I is worh noing ha, neiher males nor females performed excellen regarding hese 8 compulsory courses, as here was no a single higher han 8.5. Table 3. in Sofware Sysems compulsory courses Graduaes performance in Sofware Sysems compulsory courses Group Saisics Independen Samples Tes - Male Female T es for equaliy of means (J) Compuer Programming, I ** Sysem Programming Daa Srucures Operaing Sysems Objec Oriened Programming Sofware Technology Daabase I Human Compuer Ineracion * *The difference is significan a he 0.05 level **The difference is significan a he 0.01 level SS elecives: Graduaes Preferences The courses ha were seleced from a higher percenage of males compared o females are presened in Table 4a. Male graduaes seleced a a higher percenage 22 ou of he 28 available elecives in SS division. Those courses were mainly core programming courses (such as Java lab, C lab, C++ lab, Compilers, Parallel Programming, Theories of Programming Languages, Sofware Engineering, Curren Sofware Sysems, ec) and advanced opics of Sofware Sysems (such as Advanced opics in Programming, Advanced opics in Sofware Sysems, Advanced opics in Daabase, Advanced User Inerface ). On he conrary, females seleced a a higher percenage, compared o males, 6 ou of he 28 elecives (see Table 4b). Acually, hose 6 courses were abou sysems securiy ( Sysems securiy ) and daa and informaion managemen ( Daa and informaion Visualizaion, Techniques in machine learning & daa mining, Daabases ΙΙ, Sysem Analysis, and Informaion Rerieval ). I is also worh menioning ha very few girls (or none) seleced lab-based courses, such as 'C Lab', 'Java Lab' and 'C++ Lab' (5%, 0%, 5% respecively).

8 8 of Table 4a. Preferences and performance in Sofware Sysems elecives: courses seleced more by males Graduaes preferences and performance in Sofware Sysems elecives Group Saisics Preferences Male Female Male Female graduaes who seleced he course (%) Grade Grade Independen Samples Tes T es for equaliy of means Special opics in sofware sysems Java Lab C Lab Daa and informaion Visualizaion Info managemen on he Inerne * Sofware Engineering Advanced Topics in Daabase Advanced opics in Sof. Sysems * Curren Sofware Sysems Mulimedia Technology Daa managemen sysems C++ Lab Compilers ΙΙ Disribued Sysems Advanced opics in Programming Parallel programming Advanced User Inerfaces, VR Arificial Inelligence Informaion Sysems Inelligen Sysems & Applicaions Theories of Prog. Languages Daabase Managemen Sysems *The difference is significan a he 0.05 level SS elecives: Graduaes performance Male graduaes performed beer han females in nearly 60% of he elecives hey chose a a higher percenage han females (see Table 4a; 13 ou of he 22 courses) and more han half of elecives in SS overall (see Table 4a and 4b; 16 ou of he 28 courses). The differences in he mean s, in favor of males, ha are saisically significan regards: (a) Informaion managemen on he Inerne [males: M=8.60, =1.11; females: M=7, =1.87; (87)=2.102; p=0.030), (b) Advanced opics in Sofware Sysems [males: M=9.17, =0.80; females: M=8.29, =1.11; (34)=2.428; p=0.021], and (c) Sysems Securiy [males: M=8.41, =1.32; females: M=7, =1.56; (87)=2.345; p=0.023] (see Table,4b). Female graduaes achieved higher mean s in half of he elecives hey chose a a higher percenage compared o males (see Table 4b; 3 ou of he 6 courses) and in one hird of he elecives in SS division overall (see Table 4a and 4b; 10 ou of he 28 courses). The saisical analysis did no reveal saisical significan differences in favor of females. Finally, males and females performed equally well in 2 elecives.

9 9 of Table 4b. Preferences and performance in Sofware Sysems elecives: courses seleced more by females Graduaes preferences and performance in Sofware Sysems elecives Group Saisics Independen Samples Tes - Preferences T es for equaliy of means Male Female Male Female graduaes who seleced he Grade Grade course (%) Daa and informaion visualizaion Sysems securiy * Machine learning & daa mining Daabases ΙΙ Sysem analysis Informaion rerieval *The difference is significan a he 0.05 level Sudens Choices and in Compuer Technology and Compuer Sysems (CTCS) courses CTCS compulsory courses: Graduaes performance The performance, in erms of mean s, of male and female graduaes regarding CTCS compulsory courses are illusraed in Table 5. I seems ha male sudens performed slighly beer han females in 2 ou of he 3 courses while girls had a marginally higher mean in Compuer Archiecure I compared o males. Neverheless, hese differences in he mean s are no saisically significan. Table 5. in Compuer Technology and Compuer Sysems compulsory courses Graduaes performance in Compuer Technology and Compuer Sysems compulsory courses Groups Saisics Independen Samples Tes - Male Female T es for equaliy of means (J) Compuer Neworks I Logic Design Compuer Archiecure I CTCS elecives: Graduaes preferences Male graduaes chose a a higher percenage, compared o females, more han half of he available elecives of CTCS division (See Table 6a; 9 ou of he 15 courses). These courses are abou compuer neworks issues ( Advanced Compuer Nework Issues, Digial Signal Processing, Compuer Communicaions and Neworks II ), compuer engineering ( Synhesis of Digial Archiecures, Compuer arihmeic, Compuer organizaion, Inroducion o Hardware Descripion Languages, and Inroducion o embedded sysems ) and Roboics. Regarding female graduaes choices, hey seleced a a higher percenage, compared o males, 6 ou of he 15 elecives (see Table 6b), mainly concerning compuer archiecure ( Advanced Compuer Archiecures, Compuer Archiecure II, Hardware descripion languages II, Digial circui design ), coding and mobile communicaion ( Informaion heory and coding and Wireless and Mobile Communicaions ). Neverheless, one hird of he elecives of CTCS division were no seleced by any of he female graduaes (see Table 6a; 5 ou of he 15 courses), ha were abou compuer engineering

10 10 of ( Synhesis of digial archiecures, compuer arihmeic ), roboics ( Roboics ) and compuer nework issues ( Digial signal processing Advanced Compuer Nework Issues ). Correspondingly, 4 ou of he 15 available elecives were seleced by jus one male (see Table 6a and 6b). Table 6a. Preferences and in Compuer Technology and Compuer Sysems elecives: courses seleced more by males Graduaes preferences and performance in Compuer Technology and Compuer Sysems elecives Group Saisics Preferences Male Female Male Female graduaes who seleced he course (%) Grade Grade Independen Samples Tes - T es for equaliy of means Advanced Compuer Nework Issues Roboics Synhesis of Digial Archiecures Digial Signal Processing Compuer arihmeic Inroducion o embedded sysems Hardware Descripion Languages Compuer Neworks II Compuer organizaion CTCS elecives: Graduaes performance Male graduaes performed slighly beer compared o females in 3 elecives, apar from hose elecives ha hey were seleced jus by males. However, he mean differences in hose cases are no saisically significan. Ineresingly, male graduaes performed excepionally well in he elecives ha were no seleced by females, and excellen in Roboics and Synhesis of Digial Archiecures. On he oher hand, female graduaes achieved higher mean s han males in 7 elecives. The saisical analysis indicaed ha he difference in he mean values is saisically significan in he case of Informaion heory and coding [males: M=5.65, =0.95; females: M=6.69, =1.46; (34)=-2.148; p=0.042]. An inspecion of he mean s reveals ha here are several courses ha females perform acually well. All in all, excep he previously menioned course, i seems ha male and female graduaes performed equally well in he elecives of CTCS division. Table 6b. Preferences and in Compuer Technology and Compuer Sysems elecives: courses seleced more by females Graduaes preferences and performance in Compuer Technology and Compuer Sysems elecives Group Saisics Preferences Male Female Male Female graduaes who seleced he course (%) Grade Grade Independen Samples Tes - T es for equaliy of means Advanced Compuer Archiecures Digial circui design Hardware descripion languages II Compuer Archiecure II

11 11 of 17 Informaion heory and coding * Wireless & Mobile Communicaions *The difference is significan a he 0.05 level Graduaes in Mahemaics & Physics (M&P) courses The analysis of he s of he graduaes in M&P courses (see Table 7) reveals ha male graduaes performed beer han females in 5 ou of he 6 Mah courses whereas in Physics I female graduaes had a higher mean. The independen sample -es ha was conduced o compare he mean s of male and female graduaes in M&P courses indicaed ha here were saisically significan differences in he mean s of 2 courses: (a) Linear Algebra [males: M=6.44, =1.31; females: M=5.55, =1.06; (87)=2.782; p=0.007], and (b) Mahemaics I [males: M=6.59, =1.43; females: M=5.98, =1.27; (87)=1.728; p=0.048]. Ye, boh male and female graduaes achieved mean s in all M&P courses which are far from 8.5 ( Excellen ). Table 7. in Mahemaics & Physics compulsory courses Graduaes in Mahemaics & Physics compulsory courses Groups Saisics Independen Samples Tes - Male Female T es for equaliy of means Sd. Deviaion (J) Sd. Deviaion Linear Algebra * Prob. Theory & Saisics Mahemaics Ι * Arihmeic Analysis Mahemaics ΙΙ Physics Ι Discree Mahemaics *The difference is significan a he 0.05 level Graduaes Preferences and in General Educaion (GE) elecives GE elecives: Graduaes preferences Elecives in GE cover a wide range of subjecs ha can be applied o many differen careers and sudens can choose hem according o heir ineress. Table 8a reveals ha 6 ou of he 20 elecives in GE were seleced a higher percenage from males compared o females. Apar from he foreign languages ( English, and French ), males preferred he sudy of mahemaical models ( Game Theory ), and he markeing and managemen perspecive of informaics ( New produc and service developmen, Economic Science I ). As i is derived from Table 8b, wo hird of he elecives, 14 ou of he 20 courses, were seleced by a higher percenage of females compared o males. These courses regard Humaniies and Social Sciences ( Social and Professional Issues, Compuers and Educaion, Sociology, Psychology, Teaching of Informaics, Pedagogy, Philosophy, Cogniive Science ), CS erminology ( English Terminology, French Terminology ), CS career opporuniies ( Banking IT ) and mahemaics ( Differenial Equaion ). I is worh noing ha very few females (in some cases, none a all) choose: Inroducion o he Economic Science I & II, Game Theory, Legal issues in informaics, French and New produc and service developmen, whereas he only elecive course ha was no seleced by males was Inroducion o he Economic Science II.

12 12 of Table 8a. Preferences and in General Educaion elecives: courses seleced more by males Graduaes preferences and performance in General Educaion elecives Group Saisics Independen Samples Tes - Preferences T es for equaliy of means Male Female Male Female graduaes who seleced he Grade Grade course (%) Inroducion o Economic Science I Legal issues in informaics Game heory English French New produc & service developmen GE elecives: Graduaes performance Male graduaes performed beer, compared o females, in 9 elecives. In fac, hey performed beer in 4 ou of he 6 elecives he seleced more. The saisical analysis reveals ha here was a saisically significan difference in he mean s of males and females in Social and Professional Issues [males: M=8.46, =1.20; females: M=5.80, =1.10; (87)=4.310; p=0.001 Likewise, female graduaes performed beer, compared o males, in 9 elecives. The saisical analysis also reveals ha here was a saisically significan difference in he mean s of females and males in Differenial Equaion [males: M=7.31, =1.91; females: M=8.67, =1.78; (87)=-1.987; p= There are also 2 elecives ha boh male and female sudens have almos same mean s ( Pedagogy and Sociology ). All in all, an inspecion of he mean s reveals ha males and females performance in GE elecives was remarkable. In fac, male graduaes performed excellen (mean equal or higher han 8.5) in 7 GE elecives, while females had a mean greaer han 8,5 in 11 elecive courses. 4 of hese courses are common for boh male and female sudens. Table 8a. Preferences and in General Educaion elecives: courses seleced more by females Graduaes preferences and performance in General Educaion elecives Group Saisics Independen Samples Tes - Preferences T es for equaliy of means Male Female Male Female graduaes who seleced he Grade Grade course (%) Inroducion o Economic Science II Social and Professional Issues * English Terminology Compuers and Educaion Hisory of Compuers Pedagogics Sociology Didacics of Informaics Cogniive Science

13 13 of 17 Psychology Managemen Informaion Sysems Banking IΤ Differenial Equaion * Philosophy *The difference is significan a he 0.05 level Discussion The analysis of he daa reveals ineresing finding in erms of CS graduaes, (a) preferences and (b) performance. CS Graduaes preferences I seems ha male graduaes seleced courses mainly from he Sofware Sysems and Compuer Technology and Compuer Sysems divisions. Acually, hey seleced a a higher percenage compared o females, core programming elecives and advanced opics of Sofware Sysems. Males also preferred elecives regarding compuer nework issues, compuer engineering and roboics. From he Theoreical Compuer Science division, hey preferred applied mahemaics and heoreical CS courses, he sudy of mahemaical srucures and oher advanced opics. General Educaion elecives were no popular among male sudens, compared o females. Males seem o prefer more foreign language courses, as well as he sudy of mahemaical models, and he markeing and managemen perspecive of informaics. This fac is in accordance wih he findings of relevan sudies in STEM fields, which suppor ha males ake mahemaics, engineering, CS, and physical sciences in higher numbers compared o females (Kenway and Gough 1998; Bussey and Bandura 1999; Coley, 2001; Amelink 2009). On he oher hand, females preferred more Theoreical Compuer Science elecives han males did, and specifically he sudy of algorihms, he pracice and sudy of echniques for secure communicaion, and compuer fracals. The elecives ha females preferred more han males did from he Sofware Sysems division were abou sysems securiy and daa and informaion managemen, while he lab-based elecives was no heir choice. Moreover, females seleced more han males did elecives regarding compuer archiecure, coding and mobile communicaion. Neverheless, females did no selec almos one hird of he elecives of Compuer Technology and Compuer Sysems division, which were abou compuer engineering, roboics and compuer nework issues. However, females preferred elecives from he General Educaion caegory ha concern humaniies and social sciences, CS erminology, and CS career opporuniies. CS Graduaes performance Male graduaes performed beer bu no saisically significan han females in he majoriy of compulsory courses in all of he aforemenioned 3 divisions, as well as Mahemaics. Acually, hey performed beer in 15 ou of he 21 compulsory courses of he curriculum of he Deparmen, while he differences in he mean s ha reach saisically significance, in favor of males, concerned one core programming course, Compuer Programming I, and wo Mahemaics courses, Linear Algebra, and Mahemaics I. Despie heir beer performance in compulsory courses, males did no perform equally well in elecives. In fac, hey performed beer in half of he available elecives overall (37 ou of he 73 available elecives). Ineresingly, hey performed beer han females in more elecives of he Sofware Sysems division, wih 3 of hese differences of he mean s are saisically significan in he following courses: Informaion managemen on he Inerne, Advanced Topics in Sofware Sysems, Sysem Securiy. Males performance in Theoreical Compuer Science elecives, compared o females, was no ousanding. Even in hose courses hey had seleced a a higher percenage compared o females, heir mean s were no higher han females. Neverheless, male graduaes performed excepionally well in he elecives hey seleced from he Compuer Technology and Compuer Sysems division, and especially in hose courses ha were no seleced by females a all, like Roboics and Synhesis of Digial Archiecures where males performed excellen. Moreover, male graduaes performed beer han females in hose General Educaion

14 14 of elecives hey seleced more. Those courses covered a variey of issues regarding CS, like Game Theory, and he connecion of CS wih he real life, like economy, social and professional issues. In fac, he difference in he mean s of Social and Professional Issues were saisically significan, in favor of males. By conras, females performed beer in 6 ou of he 21 compulsory courses. Apar from Physics, he res 5 courses are disribued in he 3 divisions, hus, here is no a clear endency. Neverheless, in Sofware Sysem division, he difference in he mean s, in favor of females, in Human Compuer Ineracion, is saisically significan. I is worh noing ha females mean s in Mah courses were really low (no over 6.6), while in Physics hey achieved mean higher han males. Despie he lower mean in mos of he compulsory courses, female graduaes performed equally well, or even beer, in elecives. Specifically, females performed beer in more Theoreical Compuer Science elecives compared o males, especially hose hey seleced a a higher percenage. I is worh menioning ha, he difference beween males and females mean in Graph Theory is saisically significan in favor of females. Regarding Sofware Sysems elecives, females performed beer in compuer sysems applicaions courses, ye hese differences are no saisically significan, hus, hey canno be generalized. Moreover, females achieved lower mean s han males in he majoriy of he Compuer Technology and Compuer Sysems elecives, bu hese differences were no saisically significan, excep he mean values in he case of Informaion heory and coding which are saisically significan in favor of females. Concerning General Educaion elecives, females performed acually well, achieving excellen mean s in 11 elecives regarding Humaniies and Social Sciences as well as areas conneced wih real and professional life. Neverheless, he only saisically significan difference in favor of females- in General Educaion elecives concerned Differenial Equaion. Overall, he analysis of he daa revealed ha here were a few significan differences in he performance of males and females in specific CS courses, indicaing ha he myh abou acual gender differences in cogniive skill and academic abiliy is non-exisen. This finding is in line wih relevan sudies in STEM fields (Ding 2006; Kiran and Sungur 2012; Alkhadrawi 2015), supporing ha when differen domains are aken ino consideraion, females perform beer han males on he social aspecs of science facors and males end o perform beer han females on he consrucs of science facors (Kiran and Sungur 2012). 6. Conclusions This sudy focused on he invesigaion of gender issues in erms of undergraduaes preferences and performance in CS undergraduae courses. For he purpose of his sudy, daa from 89 degrees earned from CS sudens during a 6-year period of graduaion a he Deparmen of CS and Technology, Universiy of Peloponnese, Greece were quaniaively analyzed. The daa analysis revealed ha here were differen preferences among male/female CS graduaes, ha is in line wih relevan evidence from oher STEM fields (Bussey and Bandura 1999; Coley, 2001; Amelink 2009). In fac, males preferred more han females did core programming courses and advanced opics of Sofware Sysems, as well as courses relaed o compuer neworks, compuer engineering, roboics and courses relaed o mahemaics. In addiion, males seleced more courses relaed o he markeing and managemen perspecive of CS. By conras, females preferred more he sudy of algorihms and he courses relaed o securiy issues, as well as compuer fracals, and daa and informaion managemen, as well as compuer archiecure, and mobile communicaion. Females also preferred courses regarding humaniies and social sciences, CS erminology, and CS career opporuniies, in which hey performed excellen. However, i is worh menioning ha, females did no selec a all programming lab-based courses, compuer engineering, compuer nework issues and roboics. In erms of performance, a firs glance, i seems ha males performed beer han females in he majoriy of he compulsory courses and some of he elecives, especially regarding Sysems Sofware and Compuer Technology & Compuer Sysems, ye he differences in he mean s are no saisically significan. Though, males performed significanly beer han females in one core programming course and wo mahemaics courses, as well as, in hree elecives concerning Sofware Sysems. The performance of males in Compuer Technology and Compuer Sysems courses were

15 15 of ousanding, especially in hose elecives ha were no seleced by females, while hey acually performed significanly beer han females in Social and Professional Issues. On he oher hand, females performance in he Theoreical Compuer Science elecives hey seleced more was remarkable, and hey performed significanly beer han males in Graph Theory. Despie he higher means in compuer sysems applicaions courses compared o males, hese differences are no saisically significan, apar from Human Compuer Ineracion elecive where females performed significanly beer han males. Like males, females s in Mahemaical courses were no high, in conras o courses relaed o Humaniies and Social Sciences and real and professional life where hey performed excellen. In addiion, females achieved significanly higher mean in Differenial Equaions, an elecive course ha females seleced a a higher percenage. On he whole, i seems ha in erms of performance here are no significan differences beween he mean s of males and females in mos of he CS courses. Any saisically significan differences in performances were presen in almos equal number of courses in favor of males and females. In his sense, sriking differences in performance in CS, like oher STEM fields (Ding 2006; Kiran and Sungur 2012; Alkhadrawi 2015), are no observed, and any difference in CS are no differences in skills or abiliy bu are acually socially consruced myhs ha consiue obsacles ha hinder female success. Limiaions of he sudy: Alhough some of he resuls are in line wih he findings of oher sudies, his sudy refers o a cerain period of ime as well as a paricular CS Deparmen in Greece wih a specific curriculum and degree requiremens. Any generalizaion of hese resuls should be underaken wih cauion and be limied o counries and CS Deparmens ha have similar characerisics o hose of he paricipans in his sudy. Any research findings differing from hose of oher sudies should be handled wih he same prudence. Implicaions of he sudy: The findings of he curren sudy have no only shown implicaions for he males and females performance, bu hey have also provided informaion abou he gender gap regarding course preferences. The absence of acual significan differences in he performance of male and female graduaes seems o deconsruc he myh ha here are acual differences in cogniive skills and academic abiliy in CS, which, in some cases consiue obsacle ha hinder female paricipaion and success in he field. Neverheless, keeping in mind ha hose myhs have acual social implicaions, his sudy can conribue o he field of CS curriculum and insrucion by deermining o wha exen more effor is needed in he educaion sysem o dispel gender myhs and remove perceived boundaries wihin cerain CS career pahs. Consequenly, his sudy could lead o he incorporaion of eaching sraegies o challenge persisen myhs, abou gender differences in CS performance, and perceived obsacles abou gender and CS. Moreover, i is hoped ha his sudy provides useful insighs abou he preferences of males and females in CS, riggering an effor for he adjusmen of he CS curriculum and insrucion by CS eachers in order o adjus he conex of CS o he preferences and he ineress of females as well. Fuure research dimensions: This sudy yields ineresing research prospecs. An invesigaion of he CS eachers beliefs abou he gender gap in CS and he differences beween males and females may uncover he presence, or he absence, of he myh of gender differences in CS educaion. Subsequenly, CS eachers and sudens can be informed abou he absence of acual differences in he performance of males and females in CS in order o be aware of he socially consruced myh and he fac ha any differences are no differences in abiliy or skills. In fac, his is nex iem in he auhors research agenda. Addiionally, educaional programs ha ake ino consideraion males and females preferences in CS can be designed, implemened and evaluaed by CS eachers in secondary educaion and CS deparmens in eriary educaion in order o render every aspec of CS ineresing, appealing and fascinaing for boh males and females. 7. Maerials and Mehods The maerials and he mehod followed are described in deail in he Conex of he sudy secion. The daa were rerieved from he official records of DCS&T wihou any reference o he personal daa of he graduaes apar from heir gender.