Content area
Purpose
In a time of fake news, misinformation, and disinformation, critical thinking has become the most important skill for discerning false, incomplete, and outdated information and communication online. The study examines the effects of personal (gender, age, ethnicity, religiosity, and Big Five personality traits) and positional inequalities (education, occupational status, language proficiency) on critical thinking digital skills (CTDS) among generations X, Y, and Z.
Design/methodology/approach
An online survey was conducted among 1,495 Israeli Jews between the ages of 18 and 57, belonging to the X, Y, and Z generations.
Findings
The findings show that CTDS among Gen X were significantly lower, by a large margin, than those of the younger generations, while Gen Z reported the highest level of these skills. Multivariate analysis indicated different effect patterns of personal and positional categorical variables on CTDS. We found that the contribution of personal demographic inequalities (gender, age, ethnicity and religiosity) to the explained variance in CTDS was most pronounced in Gen Y, compared to Gen X and Gen Z. The contribution of Big Five personality traits and positional social inequalities (education, occupational status and language proficiency) to explaining CTDS was similar between Gen X and Gen Y, but much less pronounced among Gen Z.
Practical implications
Understanding the intergenerational differences in CTDS is crucial for tailoring educational approaches, promoting inclusivity, and harnessing the diverse strengths of each generation to navigate an ever-evolving digital landscape successfully.
Originality/value
First of its kind, this study combines Generational Cohort Theory with Resources and Appropriation Theory to identify which inequalities may hinder the acquisition of one of today’s most vital skills among three generations.
Introduction
As a consequence of technological advancements, globalization, and accelerated knowledge accumulation, today’s society requires a wide range of content-related skills, which incorporate a multitude of digital components (Van Laar et al., 2022). Many studies have identified essential skills necessary for the digital age, often combining expertise in specific domains (e.g. ICT, Internet, or digital) with a knowledge-based perspective (e.g. competence, literacy, or skills) (Van Laar et al., 2022). Such skills, which are necessary for education and for a broad range of occupational tasks, have been conceptualized as 21st-century digital skills (Van Laar et al., 2018, 2020). The complexities of 21st-century work, including non-routine, creative, and interactive tasks, require skilled workers to be independent thinkers, capable of generating and refining their ideas, connecting viewpoints, and also generating new input by engaging in offline and online discussions, i.e. possessing critical thinking skills (Trenerry et al., 2021). Furthermore, in these days of fake news, misinformation, and disinformation, critical thinking has become the most important skill for discerning false, incomplete, and outdated information in communication online (Balakrishnan et al., 2023).
However, systematic analysis of 21st-century digital skills reveals that critical thinking in a digital context is less studied than other digital skills (Van Laar et al., 2020). Although various components of digital skills have been described in theory (Van Deursen et al., 2016), we know relatively little about how different individual variables affect these skills (Helsper and Eynon, 2013). Moreover, the majority of articles on 21st-century digital skills describe them conceptually with little evidence of corresponding data. Because the working environment has undergone rapid and significant innovations in recent years, it is important for policy makers to understand how different groups of employees adopt required workplace skills and which factors constitute important predictors of skills in different population groups. As numerous studies have reported salient between-generational differences in various types of skills and the different factors responsible for skill acquisition in each generation (Ferreira, 2021; Gaidhani et al., 2019), the main purpose of the current study is to evaluate between-generational differences in the effects of individual variables on critical thinking digital skills (hereinafter CTDS).
Theoretical background and research hypotheses
Digital inequality and resources and appropriation theory
The digital divide approach which was based initially on inequalities in internet access, has evolved into a divide that includes differences in internet-use skills (Van Deursen and Van Dijk, 2011). In recent years, inequality in digital skills has become a key component in digital inclusion debates (Van Deursen et al., 2021), which have expanded due to the COVID-19 pandemic (Baber et al., 2022). Definitions of digital skills have shifted from a technical orientation to a broader perspective that includes content-related or higher-order skills, which were recently conceptualized as 21st-century digital skills (Van Laar et al., 2018, 2020).
Resources and Appropriation Theory by Van Dijk (2017) focuses on the distribution and allocation of resources and explains how certain groups or individuals gain access to and exploit these resources to attain power and influence over others. More particularly it examines how both personal and positional inequalities may explain the distribution and control of resources within social systems. Personal categorical inequalities frequently observed in digital inequality research are based on gender, age, race/ethnicity, religiosity (Lissitsa and Chachashvili-Bolotin, 2022), and personality traits (Chipeva et al., 2018), whereas positional categorical inequalities pertain to status in the labor market, education and cultural capital characteristics, and urban vs. rural residence (Elena-Bucea et al., 2021; Laor et al., 2019; Lissitsa, 2015).
In terms of this theory, the CTDS resource has two dimensions – the human resource (the ability to process data judgmentally and analytically) and the technological resource (the ability to use advanced tools, equipment, and technologies). Disparities in CTDS, based on personal and positional categorical inequalities, may lead to alterations and modifications of the workforce in the 21st-century labor market and may be reflected in other domains of society as well (Van Deursen et al., 2021).
Critical thinking and critical thinking digital skills
Critical thinking is the cognitive ability to carefully examine events, circumstances or thoughts, and to make informed choices about information and communications received, based on logical reflection and reasoning (Howard et al., 2015). In the digital era, with its significant socioeconomic transformations, critical thinking has become indispensable for navigating the deluge of information and discerning its negative aspects such as fake news, misinformation, and echo chambers (Balakrishnan et al., 2023; Xiao and Yang, 2023). The shift in focus from merely acquiring ICT skills to applying them critically in a global online environment, challenged by the deluge of information reflecting varied intentions and competencies, emphasizes the need to discern reliable from misleading content, especially during significant political, social, or economic events like elections, the COVID-19 crisis, or military operations (Ahmed et al., 2023; Balakrishnan et al., 2023). CTDS enable individuals to gauge online information in terms of its credibility, relevance, and accuracy, thus helping them to make informed decisions and not be led astray by misinformation and fake news (Ahmed et al., 2023). Developing CTDS is essential for engaging in meaningful online discussions, considering diverse viewpoints respectfully, and collaborating effectively with people of different backgrounds, all of which foster global understanding and cooperation (Tsang et al., 2023). CTDS foster ethical awareness in the digital realm, encouraging users to navigate privacy, data security, and digital rights issues thoughtfully, thereby promoting responsible digital citizenship (Pastor-Escuredo et al., 2022).
CTDS are essential for 21st-century workers who must navigate the digital landscape, extract and interpret valuable information, solve problems, make informed decisions, quickly learn and adapt to new digital tools, software and platforms, foster innovation, and collaborate effectively within digital environments (Van Laar et al., 2020).
Generational cohort theory
Generational cohort theory (Inglehart, 1977), contends that people who come of age in a given time period are molded by the economic, political, technological and social environment of that period. This means that throughout their lives, each cohort will adhere to the values, preferences, and opinions specific to that age. A generational cohort is often defined as those born in a 20–25 year-period, or in a period that encompasses the birth, maturation, and initial childbearing of those in the cohort (Meredith and Schewe, 1994).
The focus of the current study is on three generations: X, Y, and Z. Gen X (those born between 1964 and 1980) grew up in a period marked by economic uncertainty (the recessions of the early 1980s and 1990s) and societal uncertainty (Lyons et al., 2007). Many became independent at a young age because both parents were working or divorced. They generally seek ongoing learning and growth opportunities (Ferreira, 2021). In terms of their digital orientation, the literature considers Gen X to be “digital immigrants” (Bennett et al., 2008), who had to devote considerable time and effort to acquire digital skills. Gen X individuals are alleged to have little tolerance for bureaucracy and rules, and excel in self-reliance (Gursoy et al., 2008) and skepticism (Crumpacker and Crumpacker, 2007), which are considered to be dimensions of critical thinking skills (Kavenuke et al., 2020).
Generations Y and Z are both considered to be digital natives and digital innovators (Neijens and Voorveld, 2018). However, their formative experiences differ. Individuals born in Gen Y (born between 1981 and 1994) matured during a period of economic growth. The distinct self-perceptions and worldviews developed by Gen Y were affected by their “helicopter parents”, i.e. parents who oversaw most decisions (Trent, 2019). They were constantly told that they were special, part of the “wanted” generation, which instilled in them the belief that they could transcend their natural abilities and limitations (Rainer and Rainer, 2011). This perspective shapes their aspirations and life approach. Gen Y is characterized as being sheltered, confident, and optimistic. Gen Y is depicted as flexible, creative, and tolerant, lacking in respect for traditions, and endowed with broad but superficial knowledge (Bencsik et al., 2016). Gen Ys prefer teamwork and view colleagues as important knowledge sources (Gursoy et al., 2008). They also expect problems to be solved collectively. A task analysis of Australian Gen Ys revealed difficulties in screen reading and a tendency to miss unhighlighted content, indicating superficial web use and limited visual skills (Combes, 2021).
Gen Z (born in and after 1995) entered a world marked by recessions and other financial crises, war and threats of terror, political unrest, and the relentless gaze of social media (Adamy, 2018). At the same time, the Gen Z world is increasingly globalized with free mobility and they are more aware and informed about world events than previous generations (Benitez-Marquez et al., 2022). They have “greater freedom of expression and greater openness to understanding different kinds of people” (Francis and Hoefel, 2018, p. 2), as they have been oriented to others. Their interpersonal skills set them apart from other generations, as they have never met many of their numerous acquaintances in person (Bejtkovský, 2016). Gen Z’s thought processes focus on differentiation, emphasizing aspects that are incorrect, functioning poorly, or not meeting their criteria. Because of their preference for visual learning, Gen Z perceives the world primarily through images, photographs, and films. They require visual information to fully comprehend and engage with concepts before taking action (Kwiecińska et al., 2023). Paradoxically, Gen Z is drawn to the immediacy of social media while exhibiting a high level of distrust towards these media. Although capable of identifying and acknowledging fake news, they often do not utilize verification tools.
Personal categorical inequalities in CTDS
Demographic variables. Scholars have found indications that personal demographic characteristics influence the development of critical thinking skills:
Age. Generally, critical thinking skills are likely to improve with age (Hmad and Mohammed, 2017), as they do not develop automatically and require practice, training, and other cognitive skills to stimulate their growth (Abdelaty et al., 2021). However, studies of adults reported a non-significant correlation between age and critical thinking (Lee et al., 2020), as well as between age and CTDS (Van Laar et al., 2019).
Gender. Previous studies on critical thinking skills yielded mixed results about gender differences: US men outperformed women (Leach, 2011), Ukrainian women scored higher in inference and deduction (Shubina and Kulakli, 2019), but studies in Asian countries found no gender differences (Marni et al., 2020). The only study on CTDS from the Netherlands indicated that employed men outperformed women (Van Laar et al., 2019).
Religiosity. Research suggests religiosity negatively affects critical thinking skills, with religious individuals potentially favoring intuition over logical reasoning (Daws and Hampshire, 2017). While efforts have been made to harmonize scientific and religious values in learning and integrate critical thinking with personal beliefs (Abdurrohman and Fitriana, 2023), this relationship remains unexplored in digital contexts.
Ethnicity. Developing critical thinking skills can be challenging for immigrants due to language barriers, cultural differences, lack of exposure to critical thinking education in the countries of origin, and psychological and social difficulties caused by integration into the new society (Lissitsa and Peres, 2011). Immigrants' access to digital resources is often hindered by economic constraints or unawareness, while natives benefit from smoother CTDS acquisition due to their direct access to resources, deeper social and cultural integration, and familiarity with the language and systems (Rosenberg, 2021).
Accordingly, we may posit.
We assumed that technically savvy Gen Z members who were constantly exposed to disinformation and fake news (Pérez-Escoda et al., 2021) and spent their coming-of-age years in societal and economic uncertainty (Adamy, 2018), developed CTDS unrelated to their demographic background variables. However, this is not the case regarding digital immigrants – Gen X, who need to apply their skepticism and self-reliance (Crumpacker and Crumpacker, 2007; Gursoy et al., 2008) to the digital environment or Gen Y, who are likely to be over-confident, undervalue soft skills and have a short attention span (Bencsik et al., 2016; Combes, 2021). Thus, we may posit.
Big five personality traits
One of the leading theories of personality is the Five Factor Model (FFM) (McCrae and John, 1992), which includes five constructs: extraversion, conscientiousness, openness to new experience, agreeableness, and neuroticism. Psychologists claim that personality strongly affects a broad range of cognitive responses (Ajzen, 2005), including digital literacy (Ahmed and Rasheed, 2020). In contrast to prior studies that investigated the effects of personality traits on critical thinking skills, our study breaks new ground by specifically exploring these traits in relation to critical thinking digital skills, an innovative area of research.
Extraversion refers to the propensity to interact with the external world, by being active and sociable and deriving enjoyment from engaging with other people (Lucas et al., 2000). Studies report a positive correlation between extraversion and critical thinking. In digital settings, this tendency toward social interaction can lead extraverts to engage in online communities, forums, and collaborative platforms where they can learn from others, exchange ideas, and seek out new reliable information (Nosratinia and Sarabchian, 2013; Russo and Amnå, 2016).
Conscientiousness refers to the quality of dependability, responsibility, and concern with details (Gosling et al., 2003). Conscientiousness is linked with self-discipline and caution, which is valuable for analyzing information and making informed decisions. Conscientiousness has been found to have a positive relationship with critical thinking ability, as conscientious individuals tend to be more disciplined and careful in analyzing information (Sepahvand et al., 2016).
Openness to experience captures a person’s aptitude to try new things and to appreciate unusual ideas, perspectives, and experiences. Those scoring high on openness to experience tend to think independently, an important critical thinking trait, and not rely on tradition or norms (George and Zhou, 2001). Accordingly, evidence indicates a positive correlation between openness to experience and critical thinking (Acevedo and Hess, 2022; Clifford et al., 2004; Nosratinia and Sarabchian, 2013), as well as a positive correlation between this personality trait and engagement in different online activities (Lissitsa and Kol, 2021).
Agreeableness refers to the inclination toward cooperation, altruism, sympathy, and a willingness to help others. Agreeable individuals tend to appreciate the values and beliefs of other people (Gosling et al., 2003), which can be helpful in understanding different perspectives and thinking critically. Some research indicates that agreeableness might negatively impact critical thinking, as agreeable individuals often prioritize conforming to social norms and avoiding conflict (Acevedo and Hess, 2022).
Neuroticism reflects a predisposition to experience distress and negative emotions such as fear, sadness, loneliness, anxiety, irritability, anger, worry, dissatisfaction and low self-esteem (Jeronimus et al., 2014). Individuals displaying neurotic tendencies are generally distressed by potential loss and risks, and they are more likely to interpret ordinary situations and minor frustrations as threatening or hopelessly difficult (Goldberg, 1990). Some studies suggest a negative relationship between neuroticism and critical thinking ability, as neurotic individuals may be more prone to anxiety and negative thinking (Acevedo and Hess, 2022), which may affect the objectivity of their judgment. Others found no significant relationships (Clifford et al., 2004; Nosratinia and Sarabchian, 2013).
Accordingly, we may posit that.
Assumedly, the CTDS developed by Gen Z digital natives are less related to their personality traits, compared to older generations. They often demonstrate a high degree of adaptability and flexibility, the ability to differentiate and identify incorrect information (Kwiecińska et al., 2023), and a high level of self-directed learning, as reflected in their efforts to seek information online in order to acquire new skills (Klopotan et al., 2020). These traits are essential for developing CTDS and mitigate the importance of personality (Dimmitt, 2017). In contrast, we may assume that among digital immigrants – Gen X, the application of critical thinking to the digital environment may be related to personality traits, which may promote or suppress this process. The same may be said for the more superficial Gen Y, who experienced the transition from traditional communication methods to digital platforms (Laor and Galily, 2022). Personality traits related to effective communication and collaboration in the digital space can impact the ability of Gen Y to engage in online discussions, share ideas, and collaborate in order to critically process information. Accordingly, we may assume that.
Positional categorical inequalities in CTDS
Social class or status may be a factor in the development of critical thinking. Due to their economic resources, upper-class families have many structural opportunities such as excellent schools and summer and after-school enrichment programs which facilitate their children’s acquisition of educational capital (including critical thinking abilities) (Tsui, 2003; Lissitsa and Chachashvili-Bolotin, 2023). The “habitus” (in Bourdieu’s (2003) term) provided by upper-class families tends to provide more opportunities for intellectual engagement, creativity and problem-solving, which promote the exercise of critical thinking. Such an environment typically nurtures content-related skills from a young age. Because higher social classes tend to adopt technological advances more rapidly, they also adjust more quickly and successfully to digital environments (Van Laar et al., 2019). This rapid adaptation entails both access to technology and the ease of integrating new digital tools into their everyday practices, enhancing their digital skills (Ren et al., 2022). This combination of educational capital and higher level skills is often associated with higher class urban localities (Bürgin and Mayer, 2020), with their concentration of resources and opportunities. This correlation extends to vocational options, with more prestigious career tracks typically accessible to those with advanced skills and educational backgrounds (Abrassart and Wolter, 2020). Individuals with greater language proficiency are likely to expend less mental effort on language processing, and their better understanding of language structure bolsters critical thinking abilities, as it facilitates more complex and sophisticated engagement with texts and ideas (Manalo and Sheppard, 2016). Thus, the intersection of social class, educational opportunities, technological adaptability, and language proficiency forms a nexus that significantly impacts the cultivation and application of critical thinking skills. Accordingly, we may posit.
Consistent with Breen and Müller’s (2020) main conclusion that structural inequality is persistent, based on high-quality national survey data from the US and seven European countries among birth cohorts covering most of the twentieth century, we posit that the core mechanisms underlying the impact of positional categorical inequalities on critical thinking may persist across generations, demonstrating a lasting impact unaffected by potential variations in technological advancements, the expansion of academic education, and socio-cultural contexts. The advantage of upper-class families encompasses not only material resources but also cultural capital, fostering exposure to diverse perspectives and challenging experiences within upper-class social networks (Breen and Müller, 2020; DiMaggio, 1982). The historical consistency of these structural inequalities in shaping critical thinking development justifies the assumption that the relative contribution of positional categorical inequalities to critical thinking skills will be comparable across different generational cohorts. Accordingly, we may assume that.
Methodology
Procedure
This study is based on an online survey of Israeli Jews from three generations: Gen X, Gen Y, and Gen Z. A post addressed to potential interviewees, including a survey link, was published on various online Israeli forums of general interest by research assistants. The survey invitation explained that the research involved a questionnaire on Internet use habits.
To ensure representativeness based on generational cohort, gender, and residential area, non-probability quota sampling was employed, which provided precise control over the representation of specific characteristics in the population sample (see Acharya et al. (2013)). Each interviewee could complete the survey only once and anonymity was assured. Approximately 70% of users who opened the survey link completed the questionnaire.
The questionnaire included about 35 questions on digital skills and 20 items on the Big Five personality traits. A pilot study with 30 respondents was conducted via an online survey to test the clarity of questions, ensure respondents could find appropriate answers to closed questions, and check for any biases caused by question order.
Sample
The study was conducted among 1,495 Israeli Jews aged 18–57, of whom 544 respondents (36.4%) belong to Gen Z, 485 (32.4%) to Gen Y, and 466 (31.2%) to Gen X. The mean age of respondents was 34.4 (SD = 11.5). Of the sample, 48.2% were male. In addition, 3.1% reported less than secondary education, 24.2% had secondary education, 15.8% had some college education, and 60.0% had an academic degree. Lastly, 46.8% of the sample reported no level of religious observance, while the rest maintained some traditions (21.7%) or defined themselves as religious or ultra-orthodox (31.6%).
Measures
Dependent variable
This study measured CTDS using self-assessment, aligning with common practices to provide insights into digital skills by focusing on internet usage contexts. This method effectively balances the need for detailed skill information with the efficiency of surveys, offering a practical way to assess digital skill levels. We used a nine-item measure based on digital skill instruments (Van Laar et al., 2018), asking respondents to rate their Internet use extent for various activities on a scale from 1 (not at all) to 5 (to a very high extent). (See Table 1). The CTDS index was constructed as an average of the nine items. The reliability index, Cronbach’s alpha, was 0.95.
Independent variables
Demographic variables: age (continuous), gender, ethnicity (immigrants vs. natives), and religiosity (secular, traditional, religious, ultra-orthodox).
Big five personality traits: were measured using the reliable 20-item Mini IPIP (Donnellan et al., 2006). Respondents indicated their level of agreement with statements on a five-point Likert scale, ranging from 1 = strongly disagree to 5 = strongly agree. Internal consistency was examined using Cronbach’s alpha. The coefficient range was 0.65–0.71, displaying acceptable reliability of the measurements. For constructing the indexes, means were calculated for each factor.
Education (less than secondary, secondary, post-secondary, BA, MA, PhD), Hebrew proficiency, English proficiency (scale 1 to 5, 1 – not at all, 5 – to a very high extent), occupational status (managers and respondents working in academic occupations vs. other occupations), locality (center vs. periphery).
For descriptive statistics of the research variables, see Table 1.
Statistical analysis
Statistical analysis was conducted using SPSS-26 software. In order to explain CTDS, multiple hierarchical regressions were conducted separately for the three generations (Table 2). Personal categorical demographic variables (gender, age, religiosity and ethnicity) were entered in the first model, Big Five personality traits in the second model and positional categorical inequalities variables in the third model. The multicollinearity assumption was rejected, as the maximal VIF measure of predictors was 1.54 for Generation X, 1.57 for Generation Y and 1.67 for Generation Z. In addition, one-way ANOVA tests with Post Hoc were conducted to examine differences between the generations for the research variables. A significant difference was found between Generation X (M = 2.93, SD = 1.13), Generation Y (M = 3.59, SD = 1.07) and Generation Z (M = 3.75, SD = 0.98) in CTDS (F(2; 1,492) = −11.11, p < 0.001). For other comparisons, see Table 1.
Findings
Gen X. The hierarchical regression analysis (Table 2, Model 3) indicated that CTDS among immigrants were lower, compared to natives (beta = −0.09, p < 0.05) (in line with H1.4). H1.3 was also confirmed: the effect of age on CTDS was non-significant. Religiosity and gender did not produce significant results (p > 0.05), thus H1.1 and H1.2 were not confirmed. In line with H3.3, the findings show a positive effect of extraversion (beta = 0.18, p < 0.001) on the dependent variable. However, H3.1, H3.2, H3.4 and H3.5 were not supported by the findings: the effects of openness to experience, conscientiousness and agreeableness were non-significant, while the effect of neuroticism was surprisingly positive (beta = 0.13, p < 0.001).
In line with H5.1, we found a positive association between education and CTDS (beta = 0.16, p < 0.001). H5.3 about the positive effect of English proficiency on the dependent variable was also supported by the findings: (beta = 0.22, p < 0.001). Other variables entered in regression Model 3 did not produce significant results (p > 0.05), thus H5.2, H5.4, and H5.5 were not supported. In all, the independent variables contributed 23.7% to explaining CTDS variance.
Gen Y. In line with H1.2 we found that CTDS were higher among men, compared to women (see Table 2, Model 3) (beta = 0.10, p < 0.05). Religiosity and ethnicity did not produce significant results (p > 0.05), thus H1.1 and H1.4 were not confirmed. We found a significant negative effect of age on CTDS, so H1.3 was not supported (beta = −0.17, p < 0.001). In line with H3.2 and H3.3, the findings show a positive effect of conscientiousness (beta = 0.09, p < 0.05) and extraversion (beta = 0.13, p < 0.001) on the dependent variable. However, H3.1, H3.4 and H3.5 were not supported by the findings: the effects of agreeableness and openness to experience were non-significant, while the effect of neuroticism was surprisingly positive (beta = 0.15, p < 0.001). In line with H5.1, we found a positive association between education and CTDS (beta = 0.11, p < 0.001). H5.3 about the positive effect of English proficiency on the dependent variable was also supported by the findings: (beta = 0.15, p < 0.001). In line with H5.4, CTDS were found to be higher among managers and those who work in academic occupations, compared to others (beta = 0.17, p < 0.001). Other variables entered in regression Model 3 did not produce significant results (p > 0.05), thus H5.2 and H5.5 were not supported. The independent variables contributed 25.8% to explaining CTDS variance.
Gen Z. In line with H1.1, we found a negative association between religiosity and CTDS (see Table 2, Model 3) (beta = −0.14, p < 0.001). Gender and ethnicity did not produce significant results (p > 0.05), thus H1.2 and H1.4 were not supported. We found a significant negative effect of age on CTDS (beta = −0.13, p < 0.001), so H1.3 was not supported. The hypotheses about the effects of personality traits on CTDS were not supported by the findings. The effects of openness to experience (H3.1), conscientiousness (H3.2), extraversion (H3.3) and agreeableness (H3.4) were non-significant, while the effect of neuroticism (H3.5) was positive (beta = 0.09, p < 0.05). In line with H5.1 and H5.3, we found positive associations between education (beta = 0.12, p < 0.001), English proficiency (beta = 0.19, p < 0.001) and the dependent variable. Other variables entered in regression Model 3 did not produce significant results (p > 0.05), thus H5.2, H5.4 and H5.5 were not supported. In all, the independent variables contributed 12.3% to explaining CTDS variance.
H2 was partially supported by the findings: among Gen Y, the proportion of variance for CTDS explained by the personal categorical demographic variables was higher (ΔR2 = 0.080) than among Gen Z (ΔR2 = 0.043). However, in contrast to H2, we found a similarity between Gen X and Gen Z in the proportion of variance for CTDS explained by the personal categorical demographic variables (among both generations (ΔR2 = 0.043)). H4 was fully supported by the findings: among Gen X (ΔR2 = 0.094) and Gen Y (ΔR2 = 0.077) the proportion of variance for CTDS explained by the Big Five personality traits was higher than among Gen Z (ΔR2 = 0.025). H6 was partially supported by the findings: in line with this hypothesis, we found a similarity between Gen X and Gen Y in the proportion of variance in CTDS explained by positional categorical inequalities (in both cases close to ΔR2 = 0.100), while in contrast to the hypothesis, among Generation Z this percentage was lower (ΔR2 = 0.055).
Discussion and implications
Discussion of the results
The main purpose of the current study was to evaluate between-generational differences in the effects of personal and positional individual variables on CTDS. Our descriptive findings show that CTDS among Gen X were significantly lower, by a large margin, than among the younger generations, while Gen Z reported the highest level of these skills. Ostensibly, these findings are surprising, considering the high level of personal characteristics related to critical thinking attributed to Gen X members, such as self-reliance (Gursoy et al., 2008), skepticism (Crumpacker and Crumpacker, 2007), analytical thinking and open-mindedness (Williams and Page, 2011). One possible explanation is that the technological resource (digital skills) is as essential in CTDS as the human resource (the ability to intellectually process, skillfully conceptualize, analyze, synthesize, and evaluate information). Although there is evidence that Gen X invests time and effort to acquire digital skills (Ahn and Jung, 2016), we can assume that transferring their critical thinking literacy into the digital environment was enormously challenging for them. In contrast, for Gen Y and especially for Gen Z the human and technological resources of CTDS or, in other words, their knowledge and domain components (Van Laar et al., 2022), are fully integral and inextricable. This underscores the theoretical proposition that digital literacy, as much as critical thinking, is vital in navigating today’s information landscape, challenging the assumption that pre-digital critical thinking skills seamlessly adapt to digital contexts. Thus, technological fluency may be considered as positional inequality, playing a crucial role in CTDS, aligning with Resources and Appropriation Theory.
The multivariate analysis indicated different patterns of effects of personal and positional categorical variables on CTDS. Our findings show that Gen X immigrants reported lower CTDS, while among the younger generations the effect of ethnicity was non-significant. Immigrants from Gen X may find it more challenging to develop CTDS due to language barriers and cultural differences (Kagan and Lissitsa, 2023), compared to the more flexible, adaptable Gen Y and Z who grew up in a global culture.
A negative association between religiosity and critical thinking, previously reported in offline settings (Daws and Hampshire, 2017), was validated in this study for the digital environment among Gen Y and Z. Faith does not encourage the asking of questions, and more religious people are more likely to ignore contrary evidence and contradictions and are less likely to engage in critical reflection which relies on evidence and proof (Kirby, 2008). Gen X is the most skeptical generation (Crumpacker and Crumpacker, 2007), and it is likely that their skepticism moderates the effect of religiosity.
We found that men from Gen X and Y reported higher CTDS, compared to women, while among Gen Z the gender effect was non-significant. As efforts to promote gender equality have increased over time (Inglehart and Norris, 2003), Gen Z women grew up in a more inclusive and empowering educational environment, compared to previous generations and had more equal opportunities with men for developing CTDS.
Extraversion showed a positive association with CTDS in Generations X and Y, but this link was not significant in Gen Z. Extraverts in X and Y, benefiting from broader social networks, have access to diverse information sources, which aids them in synthesizing and critically analyzing data, an advantage less pronounced in introverts of these generations. However, for Gen Z, growing up in an era dominated by online communication and virtual collaboration (Kwiecińska et al., 2023), the digital landscape allows introverts similar opportunities to develop and exercise critical thinking skills in digital spaces.
In contrast to previous findings which suggested a possible negative relationship between neuroticism and critical thinking ability (Acevedo and Hess, 2022), we found a positive association in all three generations. Thus a digital environment makes a difference and empowers neurotic individuals: when there is no need for immediate reaction, when interaction is fragmented in time and space and can be resumed at a later time, when identity may be anonymous and often beyond monitoring, neurotics may feel less anxiety and more self-confidence, predictability and security (Hamburger and Ben-Artzi, 2000). These could further enhance their engagement and perceived effectiveness in digital critical thinking tasks, contrasting with the natural advantage that emotionally stable individuals might exhibit in more traditional, immediate interaction settings.
The Resources and Appropriation Theory posits that positional inequalities determine individuals' access to information and their capacity to obtain resources (Van Dijk, 2017). At this juncture it intersects with the theories of social class and structural inequality (Breen and Müller, 2020). Accordingly, the findings show a positive association between CTDS on the one hand, and education and English proficiency on the other among the three generational cohorts. However, the expected effect of occupational status was significant only among Gen Y and might be attributed to their career stage dynamics. Gen X, known for their adaptability (Coetzee et al., 2017), likely had to develop digital skills across various occupational levels as technology became integral to the workplace. In contrast, many in Gen Z are just beginning their careers and might not yet occupy roles demanding higher-level critical thinking. However, Gen Y, positioned between these two stages, could be experiencing a pivotal phase where occupational status closely aligns with the development and application of CTDS.
Implications for theory
Our study stands out in its significant contribution to understanding 21st-century skills, focusing on the effects of both personal and positional inequalities on CTDS. The findings underscore the importance of integrating theories of social class and structural inequality (Breen and Müller, 2020) with digital literacy efforts that target each generation distinctively to enhance critical thinking skills.
As far as we know, this was the first study to attempt to integrate Generational Cohort Theory and Resources and Appropriation Theory in order to reveal inequalities that might challenge the acquisition of one of the most important skills in the 21st-century labor market (Van Laar et al., 2020), while incorporating vital generational characteristics. This approach marks the first study to provide generational insights into CTDS. The distinct CTDS patterns observed across generations underscore the theory’s relevance in understanding the evolving nature of critical thinking skills amidst rapid technological advancements.
Our study not only sheds light on the generational differences in CTDS, but also challenges the traditional understanding of critical thinking as purely a cognitive skill. By revealing the significant role of digital competencies, our research calls for a broader educational focus that combines cognitive abilities with technological fluency, especially in preparing future generations for the demands of the 21st-century labor market. Furthermore, our research is innovative in examining the impact of personality traits on critical thinking specifically within digital contexts, yielding intriguing and novel insights.
Implications for practice
The personal and positional inequalities we found emphasize that there’s a critical need for educational and technological interventions tailored to each generation’s specific context, ensuring equitable development of CTDS across all societal segments, empowering individuals to navigate the digital age’s complexities effectively. Enhancing CTDS across generations not only prepares individuals for the complexities of the digital age and has the potential to enhance workplace productivity and individual empowerment, but also supports the development of a critically informed citizenry, capable of navigating misinformation and contributing constructively to societal discourse (Xiao and Yang, 2023).
Accordingly, this study offers essential recommendations for policymakers, educators, and stakeholders aiming to boost CTDS across generations. For Gen X, which displays a notable CTDS disadvantage, we recommend flexible, modular training tailored to their specific career and life stages, alongside culturally sensitive programs to assist immigrants to more effectively integrate digitally. Given Gen X’s lower CTDS but strong foundation in analytical thinking, businesses should introduce digital problem-solving workshops that apply Gen X’s pre-digital critical thinking skills to contemporary digital scenarios. For example, simulate a series of digital crisis management exercises that require navigating misinformation online, using Gen X’s skepticism and self-reliance to discern credible sources.
To address the disadvantage faced by introverts in developing CTDS, it’s recommended to create inclusive learning environments that cater to their unique needs. This could include self-paced online courses, resources for independent learning, and ensuring that training programs include individualized tasks and projects, allowing introverts to engage deeply with digital content in a way that aligns with their preferred style of working and learning.
In addressing Gen Y, who are in their younger and mid-career stages, our strategy includes integrating CTDS training in their professional development with a focus on career progression. The keys to this approach are gender-inclusive initiatives, mentorship, and workshops, especially vital for narrowing the digital skills gap among women in this cohort. Turning to Gen Z, the digital era’s emerging professionals with the highest CTDS levels, it is critical to continually update their skills through adaptive learning opportunities that reflect the latest digital trends and technologies to keep pace with the rapidly evolving digital landscape.
Furthermore, enhancing CTDS for Hebrew-speaking users involves making English digital content more accessible via translation tools and bilingual resources. Ultimately, cultivating a culture that values lifelong learning and adaptability in CTDS is crucial to ensure that everyone, from Generation X to Z, remains skilled and confident in the continuously transforming digital world.
Conclusions
Our study provides compelling insight into the interplay between generational dynamics and the influence of personal and positional inequalities on CTDS. We assume that Gen X’s comparative disadvantage in CTDS, relative to younger generations, might stem from their challenges in synergizing human and technological resources. In Gen X, the effects of personality traits and positional inequalities had a more marked impact on CTDS than did demographic variables. These findings may reflect the adaptability and pragmatism of Gen X (Coetzee et al., 2017), which were shaped by technological and social shifts in their formative years (Lissitsa and Laor, 2021). These, rather than their personal demographic characteristics, may have predisposed them to leverage personality traits and socio-economic contexts more effectively in developing CTDS. For Gen Y, demographic factors, personality traits, and positional inequalities influenced CTDS variance almost equally. In Gen Y, the more pronounced effects of both personal and positional inequalities could be attributed to the diversity within this group, encompassing both young and mid-career individuals with varying requirements and expectations.
In line with social stratification theories, we observed a notable similarity between Gen X and Gen Y regarding the contribution of positional inequalities for explaining CTDS. However, among Gen Z, we found a less pronounced contribution of positional inequalities compared to the two older generations, which may indicate a shift in the mechanisms driving social mobility. Historically, access to education and socioeconomic status has been primary determinants of social mobility (Breen and Müller, 2020). However, with the rise of Gen Z, characterized by unprecedented access to information and technology, new avenues for social advancement may be emerging. The democratization of information through digital channels, particularly prominent among Gen Z, has enabled access to educational resources and skill development beyond traditional institutions. Online platforms and digital communities offer opportunities for self-directed learning, potentially lessening the impact of positional inequalities on critical thinking development.
Limitations and recommendations for further research
Several limitations exist in the present study. The current study employed convenience sampling, which, while practical, limits the generalizability of our findings to broader populations. Recognizing this limitation, future research should aim to enhance external validity by employing more rigorous sampling methods. Stratified random sampling or quota sampling could be considered to ensure a sample that more accurately reflects the diverse characteristics of the broader population.
This study examined CTDS by means of the self-assessment method, while according to the literature; performance testing is a preferable method in terms of external validity (Aesaert and Van Braak, 2014). In response to this concern, future studies will benefit from integrating performance testing alongside self-assessment methods to evaluate CTDS. By comparing the congruity between perceived and actual CTDS levels, researchers can identify discrepancies or confirm the accuracy of self-assessments, offering a richer, multidimensional understanding of critical thinking abilities across generations. Additionally, incorporating performance testing could illuminate specific areas where interventions are needed to bolster critical thinking skills, further contributing to the development of targeted educational strategies.
In addition, the sample included only the Jewish population. Further research should include both Israeli Jews and Israeli Palestinians. Incorporating Israeli Palestinians into the study would not only diversify the sample but also provide a richer, more nuanced understanding of CTDS across different cultural, social, and educational backgrounds within the same geopolitical space. This broader perspective is essential for creating a comprehensive picture of CTDS in a region characterized by its diversity and complexity.
Table 1
Descriptive statistics by generational cohorts
| Generation X a | Generation Y b | Generation Z c | Total sample | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | Mean | SD | F(2; 1,492) | |
| Use the Internet to find substantiated arguments or reasoning | 2.88bc | 1.39 | 3.56ac | 1.32 | 3.75ab | 1.29 | 3.42 | 1.38 | 59.01** |
| Use the Internet to provide proof or examples of the arguments you are giving | 3.04bc | 1.36 | 3.75ac | 1.23 | 4.01ab | 1.12 | 3.62 | 1.30 | 82.04** |
| Use the Internet to give a justification for your point of view | 3.03bc | 1.32 | 3.72ac | 1.20 | 3.94ab | 1.17 | 3.58 | 1.29 | 71.71** |
| Use the Internet to put the discussion into a new perspective | 2.68bc | 1.35 | 3.35a | 1.32 | 3.49a | 1.38 | 3.19 | 1.40 | 50.13** |
| Use the Internet to ask questions to understand other people’s viewpoint | 2.96bc | 1.29 | 3.60ac | 1.23 | 3.77ab | 1.16 | 3.46 | 1.27 | 59.17** |
| Use the Internet to consider various arguments to formulate your own point of view | 3.00bc | 1.30 | 3.67ac | 1.22 | 3.84ab | 1.20 | 3.52 | 1.29 | 62.95** |
| Use the Internet to filter the most important points from discussions | 2.76bc | 1.32 | 3.41a | 1.32 | 3.48a | 1.32 | 3.23 | 1.36 | 43.65** |
| Use the Internet to justify your choices | 2.94bc | 1.32 | 3.57ac | 1.30 | 3.73ab | 1.27 | 3.43 | 1.33 | 50.35** |
| Confidence in your own ability to identify false messages and fake news | 3.06bc | 1.21 | 3.65a | 1.15 | 3.71a | 1.13 | 3.49 | 1.20 | 46.42** |
| Critical thinking digital skills (index, scale 1–5) | 2.93bc | 1.13 | 3.59ac | 1.07 | 3.75ab | 0.98 | 3.44 | 1.11 | 82.36** |
| Extraversion | 3.03bc | 0.73 | 3.15ac | 0.81 | 3.25ab | 0.83 | 3.15 | 0.80 | 9.58** |
| Agreeableness | 3.74c | 0.74 | 3.78c | 0.83 | 3.97ab | 0.78 | 3.83 | 0.79 | 13.03** |
| Consciousness | 3.73c | 0.73 | 3.66c | 0.74 | 3.52ab | 0.79 | 3.63 | 0.76 | 10.12** |
| Openness to experience | 3.61c | 0.92 | 3.68c | 0.97 | 3.80ab | 0.97 | 3.70 | 0.96 | 5.18** |
| Neuroticism | 2.55bc | 0.90 | 2.74ac | 0.94 | 2.92ab | 0.96 | 2.75 | 0.95 | 20.17** |
Note(s): *p < 0.05; **p < 0.001
Source(s): Table by author
Table 2
Summary of hierarchical regression analysis for variables predicting critical thinking digital skills among Gen X (N = 466), Gen Y (N = 485) and Gen Z (N = 544)
| Generation X | Generation Y | Generation Z | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 1 | Model 2 | Model 3 | Model 1 | Model 2 | Model 3 | ||||||||||
| B | Beta | B | Beta | B | Beta | B | Beta | B | Beta | B | Beta | B | Beta | B | Beta | B | Beta | |
| (Constant) | 4.33** | 2.16** | 0.90 | 5.64** | 3.30** | 1.58 | 4.96** | 3.93** | 2.94** | |||||||||
| Gender (1 = male) | 0.18* | 0.08 | 0.21* | 0.09 | 0.08 | 0.04 | 0.01 | 0.00 | 0.15 | 0.07 | 0.21* | 0.10 | 0.04 | 0.02 | 0.09 | 0.05 | 0.08 | 0.04 |
| Religiosity | −0.12* | −0.11 | −0.07 | −0.06 | −0.03 | −0.03 | −0.20** | −0.17 | −0.15** | −0.13 | −0.09 | −0.08 | −0.18** | −0.18 | −0.17** | −0.17 | −0.15** | −0.14 |
| Age | −0.02* | −0.10 | −0.02 | −0.08 | −0.01 | −0.04 | −0.05** | −0.21 | −0.04** | −0.17 | −0.04** | −0.17 | −0.04* | −0.08 | −0.03 | −0.08 | −0.06** | −0.13 |
| Immigrants | −0.24* | −0.08 | −0.22 | −0.08 | −0.26* | −0.09 | −0.25 | −0.07 | −0.30* | −0.09 | −0.19 | −0.06 | 0.14 | 0.04 | 0.13 | 0.04 | 0.08 | 0.02 |
| Extraversion | 0.31** | 0.20 | 0.27** | 0.18 | 0.26** | 0.19 | 0.18** | 0.13 | 0.07 | 0.06 | 0.06 | 0.05 | ||||||
| Agreeableness | 0.07 | 0.05 | 0.00 | 0.00 | 0.10 | 0.08 | 0.10 | 0.07 | 0.14* | 0.11 | 0.09 | 0.07 | ||||||
| Consciousness | −0.12 | −0.08 | −0.08 | −0.05 | 0.14* | 0.10 | 0.13* | 0.09 | −0.05 | −0.04 | −0.07 | −0.06 | ||||||
| Neuroticism | 0.20** | 0.16 | 0.16** | 0.13 | 0.17** | 0.15 | 0.17** | 0.15 | 0.10* | 0.10 | 0.09* | 0.09 | ||||||
| Openness to experience | 0.13* | 0.10 | 0.05 | 0.04 | −0.09 | −0.08 | −0.10 | −0.09 | 0.01 | 0.01 | −0.02 | −0.02 | ||||||
| Education | 0.16** | 0.16 | 0.12** | 0.11 | 0.12** | 0.12 | ||||||||||||
| Hebrew Proficiency | −0.02 | −0.01 | 0.13 | 0.07 | 0.19 | 0.08 | ||||||||||||
| English proficiency | 0.23** | 0.22 | 0.16** | 0.15 | 0.18** | 0.19 | ||||||||||||
| Locality (1 = center_) | 0.02 | 0.01 | 0.10 | 0.05 | 0.01 | 0.01 | ||||||||||||
| Occupational status (1 = Manager) | 0.17 | 0.07 | 0.37** | 0.17 | 0.07 | 0.02 | ||||||||||||
| R2 | 0.043 | 0.137 | 0.237 | 0.080 | 0.157 | 0.258 | 0.043 | 0.068 | 0.123 | |||||||||
| ΔR2 | 0.043 | 0.094 | 0.100 | 0.080 | 0.077 | 0.101 | 0.043 | 0.025 | 0.055 | |||||||||
| F | F(4; 447) = 5.05** | F(9; 442) = 7.79** | F(14; 437) = 9.71** | F(4; 465) = 10.06** | F(9; 460) = 9.34** | F(14; 455) = 11.3** | F(4; 522) = 5.92** | F(9; 517) = 4.19** | F(14; 512) = 5.14** | |||||||||
Note(s): #p < 0.1; *p < 0.05; **p < 0.001
Source(s): Table by author
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