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Psychometric Properties of Rational-Experiential Inventory for Adolescents:

Psychometric Properties of Rational-Experiential Inventory for Adolescents: This study investigates the psychometric properties of a well-set form of the Rational-Experiential Inventory (REI) for adolescents (REI-A20). Participants were 746 Iranian high school students (412 males, 334 females), selected through multistage sampling method. After subjecting our data to principal components analysis (PCA) and parallel analysis (PA), we found a two-factor structure corresponding to rational and experiential processing. Both rational and experiential scales of the REI-A20 exhibited good internal consistency. These two factors accounted for 37% of the variance. The fit indices of confirmatory factor analysis (CFA) confirmed the cross-validity of the inventory. Rationality, but not experientiality, was significantly related to better school performance, elaboration, organization, and metacognitive strategies. Males scored significantly higher on rational scale, but there was no difference between females and males in scores on experiential scale. This new inventory has reliable scores, and allows for valid inferences in assessing individual differences in adolescents’ preference for the rational and experiential information-processing styles. Keywords Rational-Experiential Inventory, information-processing style, cognitive-experiential self-theory, educational psychology, applied psychology, psychology, social sciences, educational psychology and counseling, education For example, people who prefer to process information Introduction objectively and logically may be more interested in science, Cognitive psychologists and social psychology researchers and intuitive processing of information may lead one to be know that people make decisions and respond to situations more superstitious (Epstein, 2008). by employing two different but complementary processes In psychology, the question of whether human beings rep- (Chaiken & Trope, 1999). Although in all situations, behav- resent and process information in two different modes has ior is determined jointly by two ways of processing, one way been investigated for over a century (Evans, 2003; Kahneman is often predominant. Predominance of one processing style & Frederick, 2002; Riding & Rayner, 1998). In recent years, depends on a variety of factors, including the importance of dual-process theorists have argued that human reasoning the decision, the information one has about the situation, past involves two distinct processing systems: one is quick, experiences, the extent of emotional involvement, and most effortless, associative, and intuitive, and the other is slow, importantly, the individual’s preference for relying on one effortful, analytic, and deliberate (Alter, Oppenheimer, system more than the other (Epstein, 2003; Epstein, Pacini, Epley, & Eyre, 2007; Chaiken & Trope, 1999; Evans, 2008; Denes-Raj, & Heier, 1996). Some people produce more heu- Evans & Over, 1996; Stanovich, 1999). These two process- ristic and less logical responses, while others rely more ing modes are variously referred to as “first-signal” and “sec- extensively on logical rules, weigh options, and think through ond-signal” systems (Pavlov, cited in Epstein et al., 1996), each problem thoroughly and objectively (Epstein, 2008). “implicit” and “explicit” (Reber, 1993), “system 1” and Research has shown that many people often ignore objective evidence, such as base rates or conjunction principles, and rely instead on heuristics, such as availability and represen- University of Tehran, Iran tativeness (for a review, see Fiske & Taylor, 1991; Nisbett, Corresponding Author: Krantz, Jepson, & Kunda, 1983). Our decisions, the way we Ehsan Shahghasemi, Assistant Professor, Department of Communication, see the world, and our personality are shaped by the way we University of Tehran, Ale Ahmad Ave., Tehran 1411713118, Iran. process information (Epstein, 2003; Pacini & Epstein, 1999). Email: shahghasemi@ut.ac.ir Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open “system 2” (Stanovich, 1999), “heuristic” and “analytic” Epstein and his colleagues (1996). The REI as developed by (Evans, 1989; Tversky & Kahneman, 1983), “associative” Epstein et al. (1996) contains 31 items: 19 NFC items and 12 and “rule-based” (Sloman, 1996), “nonverbal” and “verbal” FI items. The REI has been refined several times since its (Paivio, 1986), “experiential” and “rational” (Epstein, 1983), introduction. “heuristic” and “systematic” (Chaiken, 1980; Petty & Pacini and Epstein (1999) developed the most recent ver- Cacioppo, 1981), to name a few (see a review in Osman, sion of the REI with 40 items. It includes subscales of ability 2004; Smith & DeCoster, 2000). The dual-process models and engagement for both rational and experiential scales (10 generally agree upon the characterizations of the two pro- items for each subscale). This version is an improvement on cessing models (Schroyens, Schaeken, & Handley, 2003; the old version; limitations of the old version have been Stanovich & West, 2000); however, there are three main dif- eliminated. In the old version, scales did not have parallel ferences among these models: They differ to some extent in content, the NFC scale’s internal consistency (α = .87) was their focus on the role of motivation versus ability, their higher than the FI scale’s (α = .77), there were social ele- explanation of the logical and temporal relations between the ments in FI items but not in NFC items, and scales were two processing modes, and the extent to which they believe unbalanced in the number of items per scale, and in the num- there is an evaluative distinction between these two process- ber of negatively and positively worded items (Pacini & ing modes (Smith & DeCoster, 2000). Epstein, 1999). Epstein (1983, 1994) and Kirkpatrick and Epstein (1992) The REI has been used widely in recent years. Many have developed a social-cognitive theory of personality researchers have tried to adapt the scale to different popula- known as the “cognitive-experiential self-theory” (CEST). tions (Bjorklund & Backstrom, 2008; Handley et al., 2000; This theory is the only dual-process theory that places two Marks, Hine, Blore, & Phillips, 2008; Witteman, van den modes of processing in a global theory of personality (Pacini Bercken, Claes, & Godoy, 2009). Others have used it to & Epstein, 1999). A fundamental assumption in the CEST is investigate the relationship of information-processing style that there are two independent, parallel, interactive concep- to a variety of variables; for example, it has been shown that tual systems of information processing that jointly contribute rationality is more strongly and directly associated with ego to what we think, feel, and do; they are the experiential sys- strength, openness, conscientiousness, favorable basic tem and the rational system, which operate by different prin- beliefs about the self and the world, openness to experience, ciples (Epstein, 2003). According to the CEST, the rational conscientiousness, open-minded thinking, superior reason- system is intentional, logical, slow, analytic, verbal and rela- ing, academic achievement, and school performance, while it tively affect-free, and operates primarily at the conscious was most strongly and negatively related to neuroticism, level, while the experiential system is rapid, emotional, conservatism, and lack of superstitious beliefs. Moreover, holistic, automatic, preconscious, association based, nonver- experientiality is most strongly and directly associated with bal, and intimately associated with affect (Epstein, 1990, extraversion, agreeableness, favorable relationship beliefs, 1991, 1993, 2003). People are not always aware of the exis- emotional expressivity, superstitious beliefs, and poorer rea- tence of the two modes because they operate almost synchro- soning, and most strongly and inversely related to categori- nously, and only when their results are different do their cal thinking, distrust of others, and intolerance (Bertrams & different qualities become apparent (Denes-Raj & Epstein, Dickhauser, 2009; Epstein, 2003; Epstein et al., 1996; Pacini 1994; Pacini & Epstein, 1999). & Epstein, 1999; Karsai, 2009; Marks et al., 2008). As Epstein (2003) argues, if people process information Some researchers have also examined the factor structure in two ways, then it is reasonable to suspect that there are of the REI. They have shown that the factor structure is reli- differences in the efficacy with which people employ each able (test–retest and Cronbach’s alpha), and have demon- system. The important question is how to measure each sys- strated its validity (construct validity and convergent validity) tem. Many theorists have proposed and discussed two sys- for assessing individual differences in information-processing tems of processing (as noted before), but there has been a styles (Bjorklund & Backstrom, 2008; Handley et al., 2000; lack of sufficient scales to measure individual differences in Marks et al., 2008; Pacini & Epstein, 1999; Witteman et al., information-processing styles in adolescents (Epstein et al., 2009). Consistent with the assumption of the CEST, a majority 1996; Handley, Newstead, & Wright, 2000). According to of studies have found the rational and experiential scales of the the CEST, there are tangible individual differences in the REI to be uncorrelated (Handley et al., 2000; Pacini & Epstein, degree of reliance on each mode. To assess these differences, 1999). A study reported by Pacini and Epstein (1999) in the Epstein and his colleagues (1996) developed a self-report United States showed a reliable factor structure for rational measure named the “Rational-Experiential Inventory” (REI), versus experiential information processing. The distinction which consists of two scales: Need for Cognition (NFC) for between ability and engagement was strong on the Rationality rationality and Faith in Intuition (FI) for experientiality scale but not on the Experientiality scale. Many others have (Epstein et al., 1996; Pacini & Epstein, 1999). The NFC is a reported a two-factor structure for REI (e.g., Handley et al., shorter version of Cacioppo and Petty’s (1982) scale with the 2000, in England; Marks et al., 2008, in Australia; Bjorklund same name, and the FI scale is a new scale constructed by & Backsrom, 2008, in Sweden; Witteman et al., 2009, in The Shirzadifard et al. 3 Netherlands; Pacini & Epstein, 1999, in the United States). through formalized education (Epstein, 1994). Conversely, Reported Cronbach’s alphas for the scales are high and consis- experiential processing involves intuitive, holistic thinking tent across studies (Handley et al., 2000; Marks et al., 2008; that is fast, primitive, and associated with emotionality, Pacini & Epstein, 1999; Witteman et al., 2009). interpersonal relationships, and a higher capacity abstract Epstein (2003) argues that two different processing sys- thinking. The experiential process develops through life tems may lead to different feelings, thoughts, and behaviors. experiences. The old and new versions of REI indicate that He also emphasizes that these two information-processing rational system is positively associated with academic styles are valuable moderator variables for understanding achievement, and the relationship between the experiential behavior (Epstein, 1994, 2003). It is clear that a measure that system and academic achievement is negative (Epstein et has reliable scores and allows for valid inferences is needed al., 1996; Karsai, 2009). Based on previous scales, we antic- to assess thinking styles. As noted before, there are some ipate that the rational system is positively related to aca- good measures for assessing individual differences in cogni- demic achievement, and that it can be considered a valid tive systems, and the REI is one of the most popular ones. construct for the REI-A20. The REI has proven to be a well-suited scale for measur- Self-regulated learning is a multidimensional construct; ing individual differences among adults. The question to be those who learn in self-regulated mode are affectively, cog- answered is whether its psychometric properties are appro- nitively, and behaviorally engaged in their learning processes priate for adolescents in other countries with different cul- (Pintrich & de Groot, 1990). Therefore, those learners who tural contexts. Thus, our main research focus is a are highly self-regulated are mainly described as committed methodological problem: the application of the adult version participants who successfully employ various different meth- of the REI in an adolescent population. Some researchers ods to control their learning experiences; for instance, they who have used the REI in their projects have reported reli- hold constructive motivational beliefs about their capabili- ability problems in their studies of adolescent participants ties and the value of learning, maintain adaptive emotional (see, for example, Klaczynski, Fauth, & Swanger, 1998). In profiles while fulfilling academic assignments, organize and Fartash’s (2011) study using the adult version on high school rehearse information to be learned, monitor their information students in Iran, nine items were removed because of low processes, and look for help when they do have difficulties in factor loading. For this and other reasons, we think there is a understanding. Academic self-regulation needs conscious considerable need to develop a scale to investigate informa- and active awareness, coordination of the processes of cogni- tion-processing styles of adolescents. It should be noted that tive and metacognitive thought, and selection of appropriate Marks et al. (2008) developed a measure named the “REI-A” strategies directed at achieving learning goals (Duncan & for Australian adolescents. After feedback from adolescents McKeachie, 2005). We predict, based on special characteris- in pilot group interviews, they reworded some items of the tics of each processing style, that rationality will correlate original REI (Pacini & Epstein, 1999) to make them more with greater use of cognitive strategies than experientiality. comprehensible for participants. The new measure had two Studies also show that rationality relates to deep approaches, scales of rationality and experientiality. and experientiality relates to surface-based approaches to The purpose of this study was to investigate the factor learning (see, for example, Handley et al., 2000). Here, we structure and psychometric properties of a shorter version of examine the association between the REI-A20 and learning the REI for adolescents (REI-A20). In line with the CEST, strategies, as well as construct validity. these two systems are independent; hence, there might be Most studies (Handley et al., 2000; Pacini & Epstein, people who are high on both, low on both, or high on one and 1999; Sladek, Bond, & Phillips, 2010; Witteman et al., 2009) low on the other (Epstein, 1998). The new measure is, thus, have shown a gender difference in processing styles among assumed to have independent scales of rationality and adults: Males tend to score higher on the Rationality scale, experientiality. whereas females tend to score higher on Experientiality. According to Epstein (1983, 1990, 1991, 1993, 1994, These results should be regarded cautiously because not all 2003), rational and experiential systems may lead to differ- studies have reported these differences (Epstein et al., 1996; ent outcomes in real life. We further predict that the scores Handley et al., 2000). This is why we investigate this subject on the rational and experiential scales will relate differently in this study and ask the following: Is there a difference to academic performance. Academic performance is the between girls and boys in terms of their reliance on one of extent to which a student, teacher, or institution has achieved the two systems? their short- or long-term educational goals (Ward, Stoker, & Murray-Ward, 1996). Cumulative grade point average Method (GPA) and achieving educational degrees such as a high school diploma or bachelor’s degree are seen as measures of Participants academic performance. As noted before, in the rational sys- Participants were 746 high school students (412 males, 334 tem we have reasoning, concrete rules, and conscientious- females) aged between 14 and 18 (M = 15.63, SD = 0.62) ness; additionally, the rational process develops through an from 29 high schools in Tehran, Iran. We gathered data from active mode of knowledge seeking, particularly 4 SAGE Open two independent samples: The first sample consisted of 610 (2009); Hejazi, Rastegar, and Ghorban Jahromi (2009); and students (325 males, 285 females), and the second included Hejazi, Rastegar, Karamdost, and Ghorban Jahromi (2008) 136 students (87 males, 49 females) from the same popula- used confirmatory factor analysis (CFA), and confirmed the tion. The sample group was selected randomly via the multi- factor structure of the MSLQ in Iran. In these studies, Cron- stage sampling method. Students chosen with this method bach’s alphas for the subscales were .69 to .84. In this study, then decided if they were willing to participate in our study. the internal consistency coefficient for each subscale is at an Overall, the questionnaire completion procedure took acceptable level (Metacognition: α = .63, Rehearsal: α = .64, approximately 25 min. To nullify extraneous variables that Elaboration: α = 70, and Organization: α = 64). could potentially affect our study, we employed a sample method that helped us choose our participants from different Academic performance. Final GPA was used as an academic majors, ages, levels of academic performance, IQ, and so on. performance measure. Students were from different majors; thus, we standardized the scores. Final grades in Iran range from 0 to 20. Instruments REI. The REI (Pacini & Epstein, 1999) is a 40-item inven- Procedure tory that includes two main scales: Rationality (20 items) and Experientiality (20 items). Each scale contains two sub- This study is an exploratory study which aims to show the scales: Ability (10 items) and Engagement (10 items). Hence, factor structure of the REI-A20. To do so, we did our research there are four subscales: Rational Ability, which refers to in three steps: high or low levels of ability to think logically, as in “I have First, we translated the REI into Persian, and two transla- no problem thinking things through carefully”; Rational tors independently translated it back into English. We com- Engagement, which refers to levels of enjoyment of thinking pared all retranslated items carefully with those of the in an analytic manner, as in “Thinking hard and for a long original form to make sure that items are acceptably equiva- time about something gives me little satisfaction”; Experien- lent to English. We further conducted a pilot study (65 stu- tial Ability, which refers to reports of a high or low level of dents from the same population who participated in this ability in intuitive thinking, as in “I can usually feel when a study) to determine if there were items confusing to the stu- person is right or wrong, even if I can’t explain how I know”; dents. Moreover, we asked students to talk about their com- and Experiential Engagement, which refers to enjoying or prehension of the items, and then used this information to not to enjoying intuitive thinking, as in “I like to rely on my refine translated items to make them more comprehensible. intuitive impressions.” Respondents scored each item on a We briefly instructed students on how to complete the answer 5-point Likert-type scale, which ranged from 1 = completely sheet, and had them complete their sheets in the classroom in false to 5 = completely true. Pacini and Epstein (1999) a single session lasting approximately 30 min. We also asked reported that this scale has a good internal consistency students to report their GPAs for their previous semester. (Rationality, α = .90; Rational Ability, α = .83; Rational Second, we divided participants randomly into two groups Engagement, α = .84; Experientiality, α = .87; Experiential (Group A, N = 305; Group B, N = 305). Data gathered from Ability, α = .80; Experiential Engagement, α = .79), and Group A were subjected to principal components analysis many others have shown similar results (e.g., Handley et al., (PCA), and data from Group B were used to conduct CFA. 2000). Many studies have reported good evidence for the We also ran correlation and group differences tests. Finally, REI’s validity (see, for example, Handley et al., 2000; Marks data from the second sample were subjected to correlation et al., 2008; Pacini & Epstein, 1999; Witteman et al., 2009). tests between the REI-A20 and MSLQ scales (for further detail about our questionnaire, please see Appendix I). Motivated Strategies for Learning Questionnaire (MSLQ). We measured students’ strategies of learning using four sub- Results scales: a 12-item Metacognition subscale (students’ use of metacognitive strategies), a four-item Rehearsal subscale To investigate the factor structure of the new measure (the (reciting or naming items from a list to be learned), a six- REI-A20), as our first objective, we conducted a PCA extrac- item Elaboration subscale (to build internal connections tion method, followed by orthogonal (varimax) rotation. The among different parts of content), and a four-item Organiza- initial scale was a 40-item version of the REI, which is pri- tion subscale (clustering, outlining, and selecting the main marily designed to assess individual differences in informa- ideas of a passage). All four subscales were adapted from the tion-processing styles. We recoded items that were reverse MSLQ (Pintrich, Simith, Garcia, & McKeachie, 1993), scored prior to the analysis. As scree test and traditional par- which in regard to self-regulated learning is one of the most allel analysis (PA) showed a two-factor structure, we widely used measures. We can use the 15 MSLQ subscales in extracted two factors in the next analysis. We used PCA with individual or collective forms (Duncan & McKeachie, 2005). PA, using permutations of the raw data (Steger, 2006) to find Hejazi, Rastegar, Gholamali Lavasani, and Ghorban Jahromi the true number of factors. We employed a syntax developed Shirzadifard et al. 5 Table 1. Eigenvalues and Amount of Variance Explained for the REI-A20, As Well As the Eigenvalues Derived by a Traditional PA. Actual eigenvalue Average eigenvalue 95th percentile eigenvalue % variance 4.268 1.483 1.566 20.34 3.220 1.404 1.457 17.10 1.226 1.329 1.382 6.13 1.095 1.273 1.317 5.48 1.078 1.224 1.274 5.39 0.938 1.166 1.210 4.69 Note. REI-A20 = Rational-Experiential Inventory for adolescents; PA = parallel analysis. Figure 1. Plot of actual versus randomly generated eigenvalues. by O’Connor (2000) to subject the data to PA of random per- that are drawn from actual data are compared with those mutations of the raw data. Table 1 presents the first six fac- from 100 randomly produced data; factors from the actual tors and the percentage of variance explained by each. The K data with eigenvalues higher than the corresponding eigen- > 1 heuristic shows that these REI-A20 scores have five fac- values from the random data are kept. Therefore, the first tors, but we know that this rule overestimates the number of actual eigenvalue is compared with the first random eigen- factors (Zwick & Velicer, 1986; as cited in Steger, 2006). In value, the second actual eigenvalue is compared with the contrast, PA supports a two-factor structure. As Stevens second random eigenvalue, and so forth. We can easily make (1992) suggests, items loaded below 0.40 and items with low this comparison by merely studying the numbers. communalities were removed, and the 10 best loaded items Investigation of the results in Table 1 reveals that only the on each factor were selected. Then, PA, again, showed that first two actual eigenvalues are higher than those generated the 20 remaining items consisted of two factors. by PA (for both average and 95th percentile criteria), and The eigenvalues produced from random data approximate therefore we keep them. a normal distribution. A majority of applications have used Juxtaposing actual and randomly generated eigenvalues mean eigenvalues. Glorfeld (1995; cited in Steger, 2006) can prepare a clear visual comparison of the results. Figure 1 showed that using eigenvalues at the 95th percentile of the demonstrates a plot of the eigenvalues from the REI-A20 distribution leads to less overextraction than using mean along with 95th percentiles and the mean of the eigenvalues eigenvalues. It has been said that using average eigenvalues for the random data that were produced in the fashion we is analogous to setting the Type I error rate. Glorfeld (1995; explained here. PA would show keeping the two factors cited in Steger, 2006), who took it that PA has revealed a whose actual eigenvalues are above the lines representing the slight inclination to overestimate the number of factors, pro- randomly generated eigenvalues. posed that using the 95th percentile of eigenvalues produced We extracted two factors and used varimax rotation with from the random data is more conservative. The eigenvalues Kaiser normalization. Following varimax rotation, these 6 SAGE Open Table 2. Rotated Component Matrix of REI-A20. Item No. and scales Items Factor 1 Factor 2 Rational 27 Reasoning things out carefully is not one of my strong points (−) 0.74 32 I don’t like to have to do a lot of thinking (−) 0.69 39 I am not very good at solving problems that require careful logical analysis (−) 0.68 26 I enjoy intellectual challenges 0.67 40 I enjoy solving problems that require hard thinking 0.63 25 I am not that good at figuring out complicated problems (−) 0.61 4 I am not a very analytical thinker (−) 0.61 6 I try to avoid situations that require thinking in depth about something (−) 0.60 16 Thinking is not my idea of an enjoyable activity (−) 0.55 1 I have a logical mind 0.48 Experiential 11 Intuition can be a very useful way to solve problems 0.75 34 Using my gut feelings usually works well for me in figuring out problems in my life 0.68 23 I tend to use my heart as a guide for my actions 0.62 31 I think there are times when one should rely on one’s intuition 0.61 21 I hardly ever go wrong when I listen to my deepest gut feelings to find an answer 0.59 24 I often go by my instincts when deciding on a course of action 0.57 15 I don’t think it is a good idea to rely on one’s intuition for important decisions (−) 0.49 5 I trust my initial feelings about people 0.49 22 I think it is foolish to make important decisions based on feelings (−) 0.45 18 When it comes to trusting people, I can usually rely on my gut feelings 0.44 Note. Items with a minus sign (−) are reverse scored. Extraction method: Principal components analysis. Rotation method: Varimax with Kaiser normalization. REI-A20 = Rational-Experiential Inventory for adolescents. two factors clearly reflected rational and experiential infor- Root mean square errors of approximation (RMSEA) for mation-processing styles. The Kaiser–Meyer–Olkin mea- both groups are less than .06 (RMSEA = .02, .02), which sure of sampling adequacy (KMO = 0.82) and Bartlett’s test indicate a reasonable error of approximation (Hu & Bentler, (= 1,539.515) were acceptable and significant (p < .01). 1999). Expected cross-validation indices (ECVI) for both Table 2 presents the item composition of the scales together groups (ECVI = .97, .99) are less than this index for the with their factor loadings. The determinant for the matrix saturated model (ECVI = 1.38), and this, in line with was not 0, so there is no computational problem with the Jöreskog and Sörbom’s (2003) criterion, confirms cross- factor analysis. The first factor accounted for 20%, and the validity of the model. second factor accounted for 17% of the variance in the item Correlation tests showed (see Table 4) that the rational set. Both values are greater than those reported by Pacini and experiential scales were not significantly correlated and Epstein (1999) with the adult measure (19% and 15%, (r = −.09), supporting the view that these constructs are respectively). The two scales showed good internal consis- independent, in line with the CEST (Epstein, 1994). We tency (rational: α = .83; experiential: α = .76). also examined the correlation between academic perfor- We used CFA with the maximum-likelihood method mance (reported GPAs of the last term final exams) and (using Amos 16) to confirm extracted factors and investi- scores on the two scales. As presented in Table 4, experi- gate the cross-validity of the scale. To this end, the two- entiality is not related to academic performance (r = factor model (based on data from Group A) was examined −.08). However, as we predicted, rationality is positively using data from Group B. As shown in Table 3 (Model B), and significantly associated with academic performance all model fit indices indicate very good fit. Fit indices for (r = .23, p < .01). Model A (based on data from Group A) are also presented in Correlation tests on data from the second sample are pre- Table 3, so that we can compare the models for the two sented in Table 5. Rationality is significantly associated with groups. The results show that the chi-square values for these Elaboration and Metacognitive Self-Regulation (p < .01) as two groups (χ = 178.08, 160.15) are not significant. Relative deep strategies of learning. Organization also correlated with chi-squares for the two groups (χ /df = 1.18, 1.15) are less rationality but at the p < .05 level. No significant relationship than 2 (Bentler, 1990; Byrne, 1989). Comparative fit indices was found between rational and rehearsal (as a surface strat- (CFI = .98, .98) and goodness-of-fit indices (GFI = 95, 95) egy of learning) scales. In contrast, experientiality was not for the two groups are more than .90, which show a good fit. associated with other scales in this research. Shirzadifard et al. 7 Table 3. Indicators of the Model Fitness. 2 2 Model ECVI RMSEA CFI AGFI GFI χ p df χ /df A (Sample A) .974 .024 .979 .927 .947 178.076 .065 151 1.179 B (Sample B) .994 .022 .985 .927 .952 160.152 .106 139 1.152 Note. ECVI = expected cross-validation indices; RMSEA = root mean square errors of approximation; CFI = comparative fit indices; GFI = goodness-of-fit indices; AGFI = adjusted goodness-of-fit indices. Table 4. Means, Standard Deviation, and Correlations of the Rationality, Experientiality, and Academic Performance (N = 305). Academic Scales M SD Rationality Experientiality performance Rationality 3.87 0.66 Experientiality 3.05 0.60 −.09 Academic performance 18.31 1.52 .23** −.08 **p < .01. Table 5. Means, Standard Deviation, and Correlations of the Rationality, Experientiality, and MSLQ Subscales. Scales M SD 1 2 3 4 5 6 1. Rationality 3.78 0.625 2. Experientiality 3.13 0.635 −.116 3. Rehearsal 16.70 2.45 .117 .068 4. Elaboration 21.72 4.20 .314** −.044 .206* 5. Organization 12.02 3.23 .210* .027 .199* .343** 6. Metacognitive Self- 42.15 6.38 .353** .159 .221* .543** .327** Regulation Note. N = 136. MSLQ = Motivated Strategies for Learning Questionnaire. *p < .05. **p < .01. To examine gender differences in cognitive styles, we measure for adolescents, so it may not be developmentally used a t test for two independent groups. The results suitable for use in adolescent studies (Klaczynski et al., showed that there was no difference between girls and 1998; Marks et al., 2008). boys in terms of their experientiality scores (t = 0.18), The main purpose of this study was to examine the factor while scores on Rationality scale were significantly differ- structure of a new measure of dispositional reliance on, and ent (t = 3.19, p < .01); boys scored significantly higher preference for, two information-processing styles in adoles- than girls (Table 6). Effect size (d = 0.019) for this variable cent populations. The analyses conducted in this regard is too small (Cohen, 1992), despite the fact that the differ- showed that this new measure contains two independent fac- ence was significant. tors. Using PCA and PA, we showed that this new measure contains two scales, which correspond to rational and expe- riential processing. Factor analysis of the items indicated that Discussion rationality and experientiality are independent, but there was The REI (Pacini & Epstein, 1999) is a valuable measure to not a clear separation between Ability and Engagement sub- assess individual differences in information-processing scales. Factor analysis failed to produce separate factors cor- styles in adult populations. Many researchers have used this responding to ability and engagement; thus, they were related scale to investigate a variety of variables in personality enough to be combined into an overall scale. Internal consis- (Pacini & Epstein, 1999), communication (Berger & Lee, tency indicators were high and comparable with those 2007), health psychology (Saher & Lindeman, 2005), and reported elsewhere by an adult sample, and higher than those decision-making domains (Bartels, 2006). Almost all these reported by an adolescent sample (Klaczynski et al., 1998). researchers have indicated that the REI has good psycho- To validate the extracted model, we employed the cross- metric properties in adult populations. However, there is validation method. The main purpose of this method was to not enough evidence to show that it is a well-suited confirm repeatability and generalizability of the results of 8 SAGE Open Table 6. Means, Standard Deviation, and t Test for the Equality of Means. Males Females Gender Scales M SD M SD differences t d Rationality 3.95 0.67 3.78 0.64 3.19** 0.26 Experientiality 3.05 0.62 3.06 0.58 0.18 0.02 Academic performance 18.34 1.63 18.28 1.37 0.47 0.04 Note. N = 305. For males, N = 162 and df = 161; for females, N = 143 and df = 142. **p < .01. the model examination from the test sample to the learning reported different means, while others failed to find any dif- sample. The learning sample is a group that is randomly ferences in processing styles among boys and girls. selected from the population. We conducted a CFA on the As noted before, information-processing style has become data from the learning group (Group B) to examine the fit- an important factor in studies on adolescents’ problems. We ness of the new model. According to the results, there is a reviewed some studies that have shown an association good fit between data and the examined model. It showed between cognitive processing styles and coping mechanisms clearly that the model is valid and confirms the factor struc- (Compas, Connor-Smith, Saltzman, Thomsen, & Wadsworth, ture obtained from PCA. 2001), depression (Pacini, Muir, & Epstein, 1998), and other There are not many studies that have tried to relate ratio- problems. Thus, it is important to have a well-suited scale to nality and experientiality to academic performance. We were assess adolescents’ preference for rational and experiential interested in investigating the correlation of these scales to styles. educational performance. Correlation tests indicated that These results lead us to conclude that the REI-A20 has rationality, but not experientiality, is positively and signifi- good psychometrical properties, and it can be used to mea- cantly associated with academic performance; this result sure different information-processing styles among adoles- supports the idea that rationality is related to better perfor- cents. It would be very informative to investigate its mance in academic settings. As noted by Epstein (1994), relationship to other measures with the same content. It is Sladek et al. (2010), and Sinclair and Ashkanasy (2005), pro- also interesting to relate this measure to other personality and cessing systems are influenced by a range of situational and cognition measures, as did Pacini and Epstein (1999), who dispositional factors. Similar to other educational systems, used the original REI. Two scales in this new measure are not the educational system in Iran is based heavily on reasoning balanced in terms of negatively and positively worded items, and logical principles; thus, it is reasonable to expect rational and it is a problem that requires a solution in the future scores to be related to better academic performance in such a research. setting. This result, in line with previous findings, clearly It seems that schools should pay more attention to stu- supports the construct validity of the two factors (Bertrams dents’ processing styles to modify the content of tasks and & Dickhauser, 2009; Epstein et al., 1996; Karsai, 2009). styles of teaching. Based on our findings, rational processing Analyses also showed that rational processing is related to is positively related to cognitive and metacognitive strate- use of learning strategies, but experientiality is not associ- gies; this suggests that encouraging the use of these strate- ated with these strategies. The rational system is character- gies may lead students to process information more ized by effortful information processing, demanding higher rationally. levels of cognitive resources and the conscious appraisal of events (Epstein, 2003). These characteristics lead to more Appendix I intensive use of metacognitive and cognitive strategies. We employed a t test to analyze gender differences in Rational-Experiential Inventory for Adolescents information-processing styles. The results showed that girls’ (REI-A20) and boys’ means on the Experientiality scale were not sig- nificantly different, but the rationality scores of boys were Please use the following scale to answer these questions. significantly higher than those of girls. We found that the effect size for rationality was too small to be seriously con- completely false completely true sidered here. Thus, this result should be treated cautiously. 1 2 3 4 5 We believe that information-processing styles are influenced by characteristics of the context, and that our transitional society emphasizes achievement for both genders, so gender 1. Reasoning things out carefully is not one of my differences are decreasing. Some researchers have already strong points. Shirzadifard et al. 9 2. Intuition can be a very useful way to solve Organizational Behavior and Human Decision Processes, 100, 76-95. problems. Bentler, P. (1990). Comparative fit indexes in structural models. 3. I don’t like to have to do a lot of thinking. Psychology Bulletin, 107, 238-246. 4. Using my gut feelings usually works well for me in Berger, C. R., & Lee, E. (2007). Dynamic representations of threat- figuring out problems in my life. ening trends: The role of rationality and experientiality in 5. I am not very good at solving problems that require potentiating trepidation. Communication Research, 34, 53-72. careful logical analysis. Bertrams, A., & Dickhauser, O. (2009). High-school students’ 6. I tend to use my heart as a guide for my actions. need for cognition, self-control capacity, and school achieve- 7. I enjoy intellectual challenges. ment: Testing a mediation hypothesis. Learning and Individual 8. I think there are times when one should rely on one’s Differences, 19, 135-138. intuition. Bjorklund, F., & Backstrom, M. (2008). Individual differences 9. I enjoy solving problems that require hard thinking. in processing styles: Validity of the Rational-Experiential Inventory. Scandinavian Journal of Psychology, 49, 439-446. 10. I hardly ever go wrong when I listen to my deepest Byrne, B. M. (1989). A primer of LISREL: Basic applications and gut feelings to find an answer. programming for confirmatory factor analysis models. New 11. I am not that good at figuring out complicated York, NY: Springer-Verlag. problems. Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. 12. I often go by my instincts when deciding on a course Journal of Personality and Social Psychology, 42, 116-131. of action. Chaiken, S. (1980). Heuristic versus systematic information pro- 13. I am not a very analytical thinker. cessing and the use of source versus message cues in per- 14. I don’t think it is a good idea to rely on one’s intuition suasion. Journal of Personality and Social Psychology, 39, for important decisions. 752-766. 15. I try to avoid situations that require thinking in depth Chaiken, S., & Trope, Y. (1999). Dual-process theories in social about something. psychology. New York, NY: Guilford Press. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 16. I trust my initial feelings about people. 155-159. 17. Thinking is not my idea of an enjoyable activity. Compas, B. E., Connor-Smith, J. K., Saltzman, H., Thomsen, A. 18. I think it is foolish to make important decisions based H., & Wadsworth, M. E. (2001). Coping with stress during on feelings. childhood and adolescence: Problems, progress, and potential 19. I have a logical mind. in theory and research. Psychological Bulletin, 127, 87-127. 20. When it comes to trusting people, I can usually rely Denes-Raj, V., & Epstein, S. (1994). Conflict between experiential on my gut feelings. and rational processing: When people behave against their bet- ter judgment. Journal of Personality and Social Psychology, Data scheme 66, 819-829. Recode: 1, 3, 5, 11, 13, 14, 15, 17, and 18 Duncan, T. G., & McKeachie, W. J. (2005). 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In search Skokie: Scientific Software International. of counter-examples: Deductive rationality in human reason- Kahneman, D., & Frederick, S. (2002). Representativeness revis- ing. Quarterly Journal of Experimental Psychology: Human ited: Attribute substitution in intuitive judgement. In T. Experimental Psychology, 56, 1129-1145. Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and Sinclair, M., & Ashkanasy, N. M. (2005). Intuition: Myth or a deci- biases: The psychology of intuitive judgment (pp. 49-81). sion-making tool? Management Learning, 36, 353-370. Cambridge, UK: Cambridge University Press. Sladek, R. M., Bond, M. J., & Phillips, P. A. (2010). Age and Karsai, M. (2009). Distinguishing between rational and experi- gender differences in preferences for rational and experi- ential information processing styles. Wittenberg University. ential thinking. Personality and Individual Differences, 49, Available from etd.ohiolink.edu/ 907-911. Shirzadifard et al. 11 Sloman, S. A. (1996). The empirical case for two systems of rea- Witteman, C., van den Bercken, J., Claes, L., & Godoy, A. (2009). soning. Psychological Bulletin, 119, 3-22. Assessing rational and intuitive thinking styles. European Smith, E. R., & DeCoster, J. (2000). Dual-process models in Journal of Psychological Assessment, 25, 39-47. social and cognitive psychology: Conceptual integration and links to underlying memory systems. Personality and Social Psychology Review, 4, 108-131. Author Biographies Stanovich, K. E. (1999). Who is rational? Studies of individual dif- Maysam Shirzadifard is PhD in Educational Psychology from ferences in reasoning. Mahwah, NJ: Lawrence Erlbaum. University of Tehran. His main interests are educational as well as Stanovich, K. E., & West, R. F. (2000). Individual differences in pedagogic studies. reasoning: Implications for the rationality debate. Behavioral and Brain Sciences, 23, 645-726. Ehsan Shahghasemi is an assistant professor of communication at Steger, M. F. (2006). An illustration of issues in factor extraction University of Tehran. He has done works on academic misconduct, and identification of dimensionality in psychological assess- intercultural communication and communication philosophy and ment data. Journal of Personality Assessment, 86, 263-272. technology. Stevens, J. P. (1992). Applied multivariate statistics for the social Elaheh Hejazi is a professor of Educational Psychology at sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum. University of Tehran. Tversky, A., & Kahneman, D. (1983). Extensional vs. intuitive reasoning: The conjunction fallacy in probability judgment. Zahra Naghsh is an assistant professor of Educational Psychology Psychological Review, 90, 293-315. at University of Tehran. Ward, A., Stoker, H. W., & Murray-Ward, M. (1996). Achievement and ability tests-Definition of the domain. Educational Ghafar Ranjbar is MA graduate of Educational Psychology from Measurement, 2, 2-5. 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Abstract

This study investigates the psychometric properties of a well-set form of the Rational-Experiential Inventory (REI) for adolescents (REI-A20). Participants were 746 Iranian high school students (412 males, 334 females), selected through multistage sampling method. After subjecting our data to principal components analysis (PCA) and parallel analysis (PA), we found a two-factor structure corresponding to rational and experiential processing. Both rational and experiential scales of the REI-A20 exhibited good internal consistency. These two factors accounted for 37% of the variance. The fit indices of confirmatory factor analysis (CFA) confirmed the cross-validity of the inventory. Rationality, but not experientiality, was significantly related to better school performance, elaboration, organization, and metacognitive strategies. Males scored significantly higher on rational scale, but there was no difference between females and males in scores on experiential scale. This new inventory has reliable scores, and allows for valid inferences in assessing individual differences in adolescents’ preference for the rational and experiential information-processing styles. Keywords Rational-Experiential Inventory, information-processing style, cognitive-experiential self-theory, educational psychology, applied psychology, psychology, social sciences, educational psychology and counseling, education For example, people who prefer to process information Introduction objectively and logically may be more interested in science, Cognitive psychologists and social psychology researchers and intuitive processing of information may lead one to be know that people make decisions and respond to situations more superstitious (Epstein, 2008). by employing two different but complementary processes In psychology, the question of whether human beings rep- (Chaiken & Trope, 1999). Although in all situations, behav- resent and process information in two different modes has ior is determined jointly by two ways of processing, one way been investigated for over a century (Evans, 2003; Kahneman is often predominant. Predominance of one processing style & Frederick, 2002; Riding & Rayner, 1998). In recent years, depends on a variety of factors, including the importance of dual-process theorists have argued that human reasoning the decision, the information one has about the situation, past involves two distinct processing systems: one is quick, experiences, the extent of emotional involvement, and most effortless, associative, and intuitive, and the other is slow, importantly, the individual’s preference for relying on one effortful, analytic, and deliberate (Alter, Oppenheimer, system more than the other (Epstein, 2003; Epstein, Pacini, Epley, & Eyre, 2007; Chaiken & Trope, 1999; Evans, 2008; Denes-Raj, & Heier, 1996). Some people produce more heu- Evans & Over, 1996; Stanovich, 1999). These two process- ristic and less logical responses, while others rely more ing modes are variously referred to as “first-signal” and “sec- extensively on logical rules, weigh options, and think through ond-signal” systems (Pavlov, cited in Epstein et al., 1996), each problem thoroughly and objectively (Epstein, 2008). “implicit” and “explicit” (Reber, 1993), “system 1” and Research has shown that many people often ignore objective evidence, such as base rates or conjunction principles, and rely instead on heuristics, such as availability and represen- University of Tehran, Iran tativeness (for a review, see Fiske & Taylor, 1991; Nisbett, Corresponding Author: Krantz, Jepson, & Kunda, 1983). Our decisions, the way we Ehsan Shahghasemi, Assistant Professor, Department of Communication, see the world, and our personality are shaped by the way we University of Tehran, Ale Ahmad Ave., Tehran 1411713118, Iran. process information (Epstein, 2003; Pacini & Epstein, 1999). Email: shahghasemi@ut.ac.ir Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open “system 2” (Stanovich, 1999), “heuristic” and “analytic” Epstein and his colleagues (1996). The REI as developed by (Evans, 1989; Tversky & Kahneman, 1983), “associative” Epstein et al. (1996) contains 31 items: 19 NFC items and 12 and “rule-based” (Sloman, 1996), “nonverbal” and “verbal” FI items. The REI has been refined several times since its (Paivio, 1986), “experiential” and “rational” (Epstein, 1983), introduction. “heuristic” and “systematic” (Chaiken, 1980; Petty & Pacini and Epstein (1999) developed the most recent ver- Cacioppo, 1981), to name a few (see a review in Osman, sion of the REI with 40 items. It includes subscales of ability 2004; Smith & DeCoster, 2000). The dual-process models and engagement for both rational and experiential scales (10 generally agree upon the characterizations of the two pro- items for each subscale). This version is an improvement on cessing models (Schroyens, Schaeken, & Handley, 2003; the old version; limitations of the old version have been Stanovich & West, 2000); however, there are three main dif- eliminated. In the old version, scales did not have parallel ferences among these models: They differ to some extent in content, the NFC scale’s internal consistency (α = .87) was their focus on the role of motivation versus ability, their higher than the FI scale’s (α = .77), there were social ele- explanation of the logical and temporal relations between the ments in FI items but not in NFC items, and scales were two processing modes, and the extent to which they believe unbalanced in the number of items per scale, and in the num- there is an evaluative distinction between these two process- ber of negatively and positively worded items (Pacini & ing modes (Smith & DeCoster, 2000). Epstein, 1999). Epstein (1983, 1994) and Kirkpatrick and Epstein (1992) The REI has been used widely in recent years. Many have developed a social-cognitive theory of personality researchers have tried to adapt the scale to different popula- known as the “cognitive-experiential self-theory” (CEST). tions (Bjorklund & Backstrom, 2008; Handley et al., 2000; This theory is the only dual-process theory that places two Marks, Hine, Blore, & Phillips, 2008; Witteman, van den modes of processing in a global theory of personality (Pacini Bercken, Claes, & Godoy, 2009). Others have used it to & Epstein, 1999). A fundamental assumption in the CEST is investigate the relationship of information-processing style that there are two independent, parallel, interactive concep- to a variety of variables; for example, it has been shown that tual systems of information processing that jointly contribute rationality is more strongly and directly associated with ego to what we think, feel, and do; they are the experiential sys- strength, openness, conscientiousness, favorable basic tem and the rational system, which operate by different prin- beliefs about the self and the world, openness to experience, ciples (Epstein, 2003). According to the CEST, the rational conscientiousness, open-minded thinking, superior reason- system is intentional, logical, slow, analytic, verbal and rela- ing, academic achievement, and school performance, while it tively affect-free, and operates primarily at the conscious was most strongly and negatively related to neuroticism, level, while the experiential system is rapid, emotional, conservatism, and lack of superstitious beliefs. Moreover, holistic, automatic, preconscious, association based, nonver- experientiality is most strongly and directly associated with bal, and intimately associated with affect (Epstein, 1990, extraversion, agreeableness, favorable relationship beliefs, 1991, 1993, 2003). People are not always aware of the exis- emotional expressivity, superstitious beliefs, and poorer rea- tence of the two modes because they operate almost synchro- soning, and most strongly and inversely related to categori- nously, and only when their results are different do their cal thinking, distrust of others, and intolerance (Bertrams & different qualities become apparent (Denes-Raj & Epstein, Dickhauser, 2009; Epstein, 2003; Epstein et al., 1996; Pacini 1994; Pacini & Epstein, 1999). & Epstein, 1999; Karsai, 2009; Marks et al., 2008). As Epstein (2003) argues, if people process information Some researchers have also examined the factor structure in two ways, then it is reasonable to suspect that there are of the REI. They have shown that the factor structure is reli- differences in the efficacy with which people employ each able (test–retest and Cronbach’s alpha), and have demon- system. The important question is how to measure each sys- strated its validity (construct validity and convergent validity) tem. Many theorists have proposed and discussed two sys- for assessing individual differences in information-processing tems of processing (as noted before), but there has been a styles (Bjorklund & Backstrom, 2008; Handley et al., 2000; lack of sufficient scales to measure individual differences in Marks et al., 2008; Pacini & Epstein, 1999; Witteman et al., information-processing styles in adolescents (Epstein et al., 2009). Consistent with the assumption of the CEST, a majority 1996; Handley, Newstead, & Wright, 2000). According to of studies have found the rational and experiential scales of the the CEST, there are tangible individual differences in the REI to be uncorrelated (Handley et al., 2000; Pacini & Epstein, degree of reliance on each mode. To assess these differences, 1999). A study reported by Pacini and Epstein (1999) in the Epstein and his colleagues (1996) developed a self-report United States showed a reliable factor structure for rational measure named the “Rational-Experiential Inventory” (REI), versus experiential information processing. The distinction which consists of two scales: Need for Cognition (NFC) for between ability and engagement was strong on the Rationality rationality and Faith in Intuition (FI) for experientiality scale but not on the Experientiality scale. Many others have (Epstein et al., 1996; Pacini & Epstein, 1999). The NFC is a reported a two-factor structure for REI (e.g., Handley et al., shorter version of Cacioppo and Petty’s (1982) scale with the 2000, in England; Marks et al., 2008, in Australia; Bjorklund same name, and the FI scale is a new scale constructed by & Backsrom, 2008, in Sweden; Witteman et al., 2009, in The Shirzadifard et al. 3 Netherlands; Pacini & Epstein, 1999, in the United States). through formalized education (Epstein, 1994). Conversely, Reported Cronbach’s alphas for the scales are high and consis- experiential processing involves intuitive, holistic thinking tent across studies (Handley et al., 2000; Marks et al., 2008; that is fast, primitive, and associated with emotionality, Pacini & Epstein, 1999; Witteman et al., 2009). interpersonal relationships, and a higher capacity abstract Epstein (2003) argues that two different processing sys- thinking. The experiential process develops through life tems may lead to different feelings, thoughts, and behaviors. experiences. The old and new versions of REI indicate that He also emphasizes that these two information-processing rational system is positively associated with academic styles are valuable moderator variables for understanding achievement, and the relationship between the experiential behavior (Epstein, 1994, 2003). It is clear that a measure that system and academic achievement is negative (Epstein et has reliable scores and allows for valid inferences is needed al., 1996; Karsai, 2009). Based on previous scales, we antic- to assess thinking styles. As noted before, there are some ipate that the rational system is positively related to aca- good measures for assessing individual differences in cogni- demic achievement, and that it can be considered a valid tive systems, and the REI is one of the most popular ones. construct for the REI-A20. The REI has proven to be a well-suited scale for measur- Self-regulated learning is a multidimensional construct; ing individual differences among adults. The question to be those who learn in self-regulated mode are affectively, cog- answered is whether its psychometric properties are appro- nitively, and behaviorally engaged in their learning processes priate for adolescents in other countries with different cul- (Pintrich & de Groot, 1990). Therefore, those learners who tural contexts. Thus, our main research focus is a are highly self-regulated are mainly described as committed methodological problem: the application of the adult version participants who successfully employ various different meth- of the REI in an adolescent population. Some researchers ods to control their learning experiences; for instance, they who have used the REI in their projects have reported reli- hold constructive motivational beliefs about their capabili- ability problems in their studies of adolescent participants ties and the value of learning, maintain adaptive emotional (see, for example, Klaczynski, Fauth, & Swanger, 1998). In profiles while fulfilling academic assignments, organize and Fartash’s (2011) study using the adult version on high school rehearse information to be learned, monitor their information students in Iran, nine items were removed because of low processes, and look for help when they do have difficulties in factor loading. For this and other reasons, we think there is a understanding. Academic self-regulation needs conscious considerable need to develop a scale to investigate informa- and active awareness, coordination of the processes of cogni- tion-processing styles of adolescents. It should be noted that tive and metacognitive thought, and selection of appropriate Marks et al. (2008) developed a measure named the “REI-A” strategies directed at achieving learning goals (Duncan & for Australian adolescents. After feedback from adolescents McKeachie, 2005). We predict, based on special characteris- in pilot group interviews, they reworded some items of the tics of each processing style, that rationality will correlate original REI (Pacini & Epstein, 1999) to make them more with greater use of cognitive strategies than experientiality. comprehensible for participants. The new measure had two Studies also show that rationality relates to deep approaches, scales of rationality and experientiality. and experientiality relates to surface-based approaches to The purpose of this study was to investigate the factor learning (see, for example, Handley et al., 2000). Here, we structure and psychometric properties of a shorter version of examine the association between the REI-A20 and learning the REI for adolescents (REI-A20). In line with the CEST, strategies, as well as construct validity. these two systems are independent; hence, there might be Most studies (Handley et al., 2000; Pacini & Epstein, people who are high on both, low on both, or high on one and 1999; Sladek, Bond, & Phillips, 2010; Witteman et al., 2009) low on the other (Epstein, 1998). The new measure is, thus, have shown a gender difference in processing styles among assumed to have independent scales of rationality and adults: Males tend to score higher on the Rationality scale, experientiality. whereas females tend to score higher on Experientiality. According to Epstein (1983, 1990, 1991, 1993, 1994, These results should be regarded cautiously because not all 2003), rational and experiential systems may lead to differ- studies have reported these differences (Epstein et al., 1996; ent outcomes in real life. We further predict that the scores Handley et al., 2000). This is why we investigate this subject on the rational and experiential scales will relate differently in this study and ask the following: Is there a difference to academic performance. Academic performance is the between girls and boys in terms of their reliance on one of extent to which a student, teacher, or institution has achieved the two systems? their short- or long-term educational goals (Ward, Stoker, & Murray-Ward, 1996). Cumulative grade point average Method (GPA) and achieving educational degrees such as a high school diploma or bachelor’s degree are seen as measures of Participants academic performance. As noted before, in the rational sys- Participants were 746 high school students (412 males, 334 tem we have reasoning, concrete rules, and conscientious- females) aged between 14 and 18 (M = 15.63, SD = 0.62) ness; additionally, the rational process develops through an from 29 high schools in Tehran, Iran. We gathered data from active mode of knowledge seeking, particularly 4 SAGE Open two independent samples: The first sample consisted of 610 (2009); Hejazi, Rastegar, and Ghorban Jahromi (2009); and students (325 males, 285 females), and the second included Hejazi, Rastegar, Karamdost, and Ghorban Jahromi (2008) 136 students (87 males, 49 females) from the same popula- used confirmatory factor analysis (CFA), and confirmed the tion. The sample group was selected randomly via the multi- factor structure of the MSLQ in Iran. In these studies, Cron- stage sampling method. Students chosen with this method bach’s alphas for the subscales were .69 to .84. In this study, then decided if they were willing to participate in our study. the internal consistency coefficient for each subscale is at an Overall, the questionnaire completion procedure took acceptable level (Metacognition: α = .63, Rehearsal: α = .64, approximately 25 min. To nullify extraneous variables that Elaboration: α = 70, and Organization: α = 64). could potentially affect our study, we employed a sample method that helped us choose our participants from different Academic performance. Final GPA was used as an academic majors, ages, levels of academic performance, IQ, and so on. performance measure. Students were from different majors; thus, we standardized the scores. Final grades in Iran range from 0 to 20. Instruments REI. The REI (Pacini & Epstein, 1999) is a 40-item inven- Procedure tory that includes two main scales: Rationality (20 items) and Experientiality (20 items). Each scale contains two sub- This study is an exploratory study which aims to show the scales: Ability (10 items) and Engagement (10 items). Hence, factor structure of the REI-A20. To do so, we did our research there are four subscales: Rational Ability, which refers to in three steps: high or low levels of ability to think logically, as in “I have First, we translated the REI into Persian, and two transla- no problem thinking things through carefully”; Rational tors independently translated it back into English. We com- Engagement, which refers to levels of enjoyment of thinking pared all retranslated items carefully with those of the in an analytic manner, as in “Thinking hard and for a long original form to make sure that items are acceptably equiva- time about something gives me little satisfaction”; Experien- lent to English. We further conducted a pilot study (65 stu- tial Ability, which refers to reports of a high or low level of dents from the same population who participated in this ability in intuitive thinking, as in “I can usually feel when a study) to determine if there were items confusing to the stu- person is right or wrong, even if I can’t explain how I know”; dents. Moreover, we asked students to talk about their com- and Experiential Engagement, which refers to enjoying or prehension of the items, and then used this information to not to enjoying intuitive thinking, as in “I like to rely on my refine translated items to make them more comprehensible. intuitive impressions.” Respondents scored each item on a We briefly instructed students on how to complete the answer 5-point Likert-type scale, which ranged from 1 = completely sheet, and had them complete their sheets in the classroom in false to 5 = completely true. Pacini and Epstein (1999) a single session lasting approximately 30 min. We also asked reported that this scale has a good internal consistency students to report their GPAs for their previous semester. (Rationality, α = .90; Rational Ability, α = .83; Rational Second, we divided participants randomly into two groups Engagement, α = .84; Experientiality, α = .87; Experiential (Group A, N = 305; Group B, N = 305). Data gathered from Ability, α = .80; Experiential Engagement, α = .79), and Group A were subjected to principal components analysis many others have shown similar results (e.g., Handley et al., (PCA), and data from Group B were used to conduct CFA. 2000). Many studies have reported good evidence for the We also ran correlation and group differences tests. Finally, REI’s validity (see, for example, Handley et al., 2000; Marks data from the second sample were subjected to correlation et al., 2008; Pacini & Epstein, 1999; Witteman et al., 2009). tests between the REI-A20 and MSLQ scales (for further detail about our questionnaire, please see Appendix I). Motivated Strategies for Learning Questionnaire (MSLQ). We measured students’ strategies of learning using four sub- Results scales: a 12-item Metacognition subscale (students’ use of metacognitive strategies), a four-item Rehearsal subscale To investigate the factor structure of the new measure (the (reciting or naming items from a list to be learned), a six- REI-A20), as our first objective, we conducted a PCA extrac- item Elaboration subscale (to build internal connections tion method, followed by orthogonal (varimax) rotation. The among different parts of content), and a four-item Organiza- initial scale was a 40-item version of the REI, which is pri- tion subscale (clustering, outlining, and selecting the main marily designed to assess individual differences in informa- ideas of a passage). All four subscales were adapted from the tion-processing styles. We recoded items that were reverse MSLQ (Pintrich, Simith, Garcia, & McKeachie, 1993), scored prior to the analysis. As scree test and traditional par- which in regard to self-regulated learning is one of the most allel analysis (PA) showed a two-factor structure, we widely used measures. We can use the 15 MSLQ subscales in extracted two factors in the next analysis. We used PCA with individual or collective forms (Duncan & McKeachie, 2005). PA, using permutations of the raw data (Steger, 2006) to find Hejazi, Rastegar, Gholamali Lavasani, and Ghorban Jahromi the true number of factors. We employed a syntax developed Shirzadifard et al. 5 Table 1. Eigenvalues and Amount of Variance Explained for the REI-A20, As Well As the Eigenvalues Derived by a Traditional PA. Actual eigenvalue Average eigenvalue 95th percentile eigenvalue % variance 4.268 1.483 1.566 20.34 3.220 1.404 1.457 17.10 1.226 1.329 1.382 6.13 1.095 1.273 1.317 5.48 1.078 1.224 1.274 5.39 0.938 1.166 1.210 4.69 Note. REI-A20 = Rational-Experiential Inventory for adolescents; PA = parallel analysis. Figure 1. Plot of actual versus randomly generated eigenvalues. by O’Connor (2000) to subject the data to PA of random per- that are drawn from actual data are compared with those mutations of the raw data. Table 1 presents the first six fac- from 100 randomly produced data; factors from the actual tors and the percentage of variance explained by each. The K data with eigenvalues higher than the corresponding eigen- > 1 heuristic shows that these REI-A20 scores have five fac- values from the random data are kept. Therefore, the first tors, but we know that this rule overestimates the number of actual eigenvalue is compared with the first random eigen- factors (Zwick & Velicer, 1986; as cited in Steger, 2006). In value, the second actual eigenvalue is compared with the contrast, PA supports a two-factor structure. As Stevens second random eigenvalue, and so forth. We can easily make (1992) suggests, items loaded below 0.40 and items with low this comparison by merely studying the numbers. communalities were removed, and the 10 best loaded items Investigation of the results in Table 1 reveals that only the on each factor were selected. Then, PA, again, showed that first two actual eigenvalues are higher than those generated the 20 remaining items consisted of two factors. by PA (for both average and 95th percentile criteria), and The eigenvalues produced from random data approximate therefore we keep them. a normal distribution. A majority of applications have used Juxtaposing actual and randomly generated eigenvalues mean eigenvalues. Glorfeld (1995; cited in Steger, 2006) can prepare a clear visual comparison of the results. Figure 1 showed that using eigenvalues at the 95th percentile of the demonstrates a plot of the eigenvalues from the REI-A20 distribution leads to less overextraction than using mean along with 95th percentiles and the mean of the eigenvalues eigenvalues. It has been said that using average eigenvalues for the random data that were produced in the fashion we is analogous to setting the Type I error rate. Glorfeld (1995; explained here. PA would show keeping the two factors cited in Steger, 2006), who took it that PA has revealed a whose actual eigenvalues are above the lines representing the slight inclination to overestimate the number of factors, pro- randomly generated eigenvalues. posed that using the 95th percentile of eigenvalues produced We extracted two factors and used varimax rotation with from the random data is more conservative. The eigenvalues Kaiser normalization. Following varimax rotation, these 6 SAGE Open Table 2. Rotated Component Matrix of REI-A20. Item No. and scales Items Factor 1 Factor 2 Rational 27 Reasoning things out carefully is not one of my strong points (−) 0.74 32 I don’t like to have to do a lot of thinking (−) 0.69 39 I am not very good at solving problems that require careful logical analysis (−) 0.68 26 I enjoy intellectual challenges 0.67 40 I enjoy solving problems that require hard thinking 0.63 25 I am not that good at figuring out complicated problems (−) 0.61 4 I am not a very analytical thinker (−) 0.61 6 I try to avoid situations that require thinking in depth about something (−) 0.60 16 Thinking is not my idea of an enjoyable activity (−) 0.55 1 I have a logical mind 0.48 Experiential 11 Intuition can be a very useful way to solve problems 0.75 34 Using my gut feelings usually works well for me in figuring out problems in my life 0.68 23 I tend to use my heart as a guide for my actions 0.62 31 I think there are times when one should rely on one’s intuition 0.61 21 I hardly ever go wrong when I listen to my deepest gut feelings to find an answer 0.59 24 I often go by my instincts when deciding on a course of action 0.57 15 I don’t think it is a good idea to rely on one’s intuition for important decisions (−) 0.49 5 I trust my initial feelings about people 0.49 22 I think it is foolish to make important decisions based on feelings (−) 0.45 18 When it comes to trusting people, I can usually rely on my gut feelings 0.44 Note. Items with a minus sign (−) are reverse scored. Extraction method: Principal components analysis. Rotation method: Varimax with Kaiser normalization. REI-A20 = Rational-Experiential Inventory for adolescents. two factors clearly reflected rational and experiential infor- Root mean square errors of approximation (RMSEA) for mation-processing styles. The Kaiser–Meyer–Olkin mea- both groups are less than .06 (RMSEA = .02, .02), which sure of sampling adequacy (KMO = 0.82) and Bartlett’s test indicate a reasonable error of approximation (Hu & Bentler, (= 1,539.515) were acceptable and significant (p < .01). 1999). Expected cross-validation indices (ECVI) for both Table 2 presents the item composition of the scales together groups (ECVI = .97, .99) are less than this index for the with their factor loadings. The determinant for the matrix saturated model (ECVI = 1.38), and this, in line with was not 0, so there is no computational problem with the Jöreskog and Sörbom’s (2003) criterion, confirms cross- factor analysis. The first factor accounted for 20%, and the validity of the model. second factor accounted for 17% of the variance in the item Correlation tests showed (see Table 4) that the rational set. Both values are greater than those reported by Pacini and experiential scales were not significantly correlated and Epstein (1999) with the adult measure (19% and 15%, (r = −.09), supporting the view that these constructs are respectively). The two scales showed good internal consis- independent, in line with the CEST (Epstein, 1994). We tency (rational: α = .83; experiential: α = .76). also examined the correlation between academic perfor- We used CFA with the maximum-likelihood method mance (reported GPAs of the last term final exams) and (using Amos 16) to confirm extracted factors and investi- scores on the two scales. As presented in Table 4, experi- gate the cross-validity of the scale. To this end, the two- entiality is not related to academic performance (r = factor model (based on data from Group A) was examined −.08). However, as we predicted, rationality is positively using data from Group B. As shown in Table 3 (Model B), and significantly associated with academic performance all model fit indices indicate very good fit. Fit indices for (r = .23, p < .01). Model A (based on data from Group A) are also presented in Correlation tests on data from the second sample are pre- Table 3, so that we can compare the models for the two sented in Table 5. Rationality is significantly associated with groups. The results show that the chi-square values for these Elaboration and Metacognitive Self-Regulation (p < .01) as two groups (χ = 178.08, 160.15) are not significant. Relative deep strategies of learning. Organization also correlated with chi-squares for the two groups (χ /df = 1.18, 1.15) are less rationality but at the p < .05 level. No significant relationship than 2 (Bentler, 1990; Byrne, 1989). Comparative fit indices was found between rational and rehearsal (as a surface strat- (CFI = .98, .98) and goodness-of-fit indices (GFI = 95, 95) egy of learning) scales. In contrast, experientiality was not for the two groups are more than .90, which show a good fit. associated with other scales in this research. Shirzadifard et al. 7 Table 3. Indicators of the Model Fitness. 2 2 Model ECVI RMSEA CFI AGFI GFI χ p df χ /df A (Sample A) .974 .024 .979 .927 .947 178.076 .065 151 1.179 B (Sample B) .994 .022 .985 .927 .952 160.152 .106 139 1.152 Note. ECVI = expected cross-validation indices; RMSEA = root mean square errors of approximation; CFI = comparative fit indices; GFI = goodness-of-fit indices; AGFI = adjusted goodness-of-fit indices. Table 4. Means, Standard Deviation, and Correlations of the Rationality, Experientiality, and Academic Performance (N = 305). Academic Scales M SD Rationality Experientiality performance Rationality 3.87 0.66 Experientiality 3.05 0.60 −.09 Academic performance 18.31 1.52 .23** −.08 **p < .01. Table 5. Means, Standard Deviation, and Correlations of the Rationality, Experientiality, and MSLQ Subscales. Scales M SD 1 2 3 4 5 6 1. Rationality 3.78 0.625 2. Experientiality 3.13 0.635 −.116 3. Rehearsal 16.70 2.45 .117 .068 4. Elaboration 21.72 4.20 .314** −.044 .206* 5. Organization 12.02 3.23 .210* .027 .199* .343** 6. Metacognitive Self- 42.15 6.38 .353** .159 .221* .543** .327** Regulation Note. N = 136. MSLQ = Motivated Strategies for Learning Questionnaire. *p < .05. **p < .01. To examine gender differences in cognitive styles, we measure for adolescents, so it may not be developmentally used a t test for two independent groups. The results suitable for use in adolescent studies (Klaczynski et al., showed that there was no difference between girls and 1998; Marks et al., 2008). boys in terms of their experientiality scores (t = 0.18), The main purpose of this study was to examine the factor while scores on Rationality scale were significantly differ- structure of a new measure of dispositional reliance on, and ent (t = 3.19, p < .01); boys scored significantly higher preference for, two information-processing styles in adoles- than girls (Table 6). Effect size (d = 0.019) for this variable cent populations. The analyses conducted in this regard is too small (Cohen, 1992), despite the fact that the differ- showed that this new measure contains two independent fac- ence was significant. tors. Using PCA and PA, we showed that this new measure contains two scales, which correspond to rational and expe- riential processing. Factor analysis of the items indicated that Discussion rationality and experientiality are independent, but there was The REI (Pacini & Epstein, 1999) is a valuable measure to not a clear separation between Ability and Engagement sub- assess individual differences in information-processing scales. Factor analysis failed to produce separate factors cor- styles in adult populations. Many researchers have used this responding to ability and engagement; thus, they were related scale to investigate a variety of variables in personality enough to be combined into an overall scale. Internal consis- (Pacini & Epstein, 1999), communication (Berger & Lee, tency indicators were high and comparable with those 2007), health psychology (Saher & Lindeman, 2005), and reported elsewhere by an adult sample, and higher than those decision-making domains (Bartels, 2006). Almost all these reported by an adolescent sample (Klaczynski et al., 1998). researchers have indicated that the REI has good psycho- To validate the extracted model, we employed the cross- metric properties in adult populations. However, there is validation method. The main purpose of this method was to not enough evidence to show that it is a well-suited confirm repeatability and generalizability of the results of 8 SAGE Open Table 6. Means, Standard Deviation, and t Test for the Equality of Means. Males Females Gender Scales M SD M SD differences t d Rationality 3.95 0.67 3.78 0.64 3.19** 0.26 Experientiality 3.05 0.62 3.06 0.58 0.18 0.02 Academic performance 18.34 1.63 18.28 1.37 0.47 0.04 Note. N = 305. For males, N = 162 and df = 161; for females, N = 143 and df = 142. **p < .01. the model examination from the test sample to the learning reported different means, while others failed to find any dif- sample. The learning sample is a group that is randomly ferences in processing styles among boys and girls. selected from the population. We conducted a CFA on the As noted before, information-processing style has become data from the learning group (Group B) to examine the fit- an important factor in studies on adolescents’ problems. We ness of the new model. According to the results, there is a reviewed some studies that have shown an association good fit between data and the examined model. It showed between cognitive processing styles and coping mechanisms clearly that the model is valid and confirms the factor struc- (Compas, Connor-Smith, Saltzman, Thomsen, & Wadsworth, ture obtained from PCA. 2001), depression (Pacini, Muir, & Epstein, 1998), and other There are not many studies that have tried to relate ratio- problems. Thus, it is important to have a well-suited scale to nality and experientiality to academic performance. We were assess adolescents’ preference for rational and experiential interested in investigating the correlation of these scales to styles. educational performance. Correlation tests indicated that These results lead us to conclude that the REI-A20 has rationality, but not experientiality, is positively and signifi- good psychometrical properties, and it can be used to mea- cantly associated with academic performance; this result sure different information-processing styles among adoles- supports the idea that rationality is related to better perfor- cents. It would be very informative to investigate its mance in academic settings. As noted by Epstein (1994), relationship to other measures with the same content. It is Sladek et al. (2010), and Sinclair and Ashkanasy (2005), pro- also interesting to relate this measure to other personality and cessing systems are influenced by a range of situational and cognition measures, as did Pacini and Epstein (1999), who dispositional factors. Similar to other educational systems, used the original REI. Two scales in this new measure are not the educational system in Iran is based heavily on reasoning balanced in terms of negatively and positively worded items, and logical principles; thus, it is reasonable to expect rational and it is a problem that requires a solution in the future scores to be related to better academic performance in such a research. setting. This result, in line with previous findings, clearly It seems that schools should pay more attention to stu- supports the construct validity of the two factors (Bertrams dents’ processing styles to modify the content of tasks and & Dickhauser, 2009; Epstein et al., 1996; Karsai, 2009). styles of teaching. Based on our findings, rational processing Analyses also showed that rational processing is related to is positively related to cognitive and metacognitive strate- use of learning strategies, but experientiality is not associ- gies; this suggests that encouraging the use of these strate- ated with these strategies. The rational system is character- gies may lead students to process information more ized by effortful information processing, demanding higher rationally. levels of cognitive resources and the conscious appraisal of events (Epstein, 2003). These characteristics lead to more Appendix I intensive use of metacognitive and cognitive strategies. We employed a t test to analyze gender differences in Rational-Experiential Inventory for Adolescents information-processing styles. The results showed that girls’ (REI-A20) and boys’ means on the Experientiality scale were not sig- nificantly different, but the rationality scores of boys were Please use the following scale to answer these questions. significantly higher than those of girls. We found that the effect size for rationality was too small to be seriously con- completely false completely true sidered here. Thus, this result should be treated cautiously. 1 2 3 4 5 We believe that information-processing styles are influenced by characteristics of the context, and that our transitional society emphasizes achievement for both genders, so gender 1. Reasoning things out carefully is not one of my differences are decreasing. Some researchers have already strong points. Shirzadifard et al. 9 2. Intuition can be a very useful way to solve Organizational Behavior and Human Decision Processes, 100, 76-95. problems. Bentler, P. (1990). Comparative fit indexes in structural models. 3. 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(1996). The empirical case for two systems of rea- Witteman, C., van den Bercken, J., Claes, L., & Godoy, A. (2009). soning. Psychological Bulletin, 119, 3-22. Assessing rational and intuitive thinking styles. European Smith, E. R., & DeCoster, J. (2000). Dual-process models in Journal of Psychological Assessment, 25, 39-47. social and cognitive psychology: Conceptual integration and links to underlying memory systems. Personality and Social Psychology Review, 4, 108-131. Author Biographies Stanovich, K. E. (1999). Who is rational? Studies of individual dif- Maysam Shirzadifard is PhD in Educational Psychology from ferences in reasoning. Mahwah, NJ: Lawrence Erlbaum. University of Tehran. His main interests are educational as well as Stanovich, K. E., & West, R. F. (2000). Individual differences in pedagogic studies. reasoning: Implications for the rationality debate. Behavioral and Brain Sciences, 23, 645-726. Ehsan Shahghasemi is an assistant professor of communication at Steger, M. 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SAGE OpenSAGE

Published: Mar 28, 2018

Keywords: Rational-Experiential Inventory; information-processing style; cognitive-experiential self-theory; educational psychology; applied psychology; psychology; social sciences; educational psychology and counseling; education

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