359 Studies in Second Language Learning and Teaching Department of English Studies, Faculty of Pedagogy and Fine Arts, Adam Mickiewicz University, Kalisz SSLLT 10 (2). 2020. 359-384 http://dx.doi.org/10.14746/ssllt.2020.10.2.7 http://pressto.amu.edu.pl/index.php/ssllt Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and multiple intelligences Sholeh Moradi Shahid Bahonar University of Kerman, Kerman, Iran https://orcid.org/0000-0003-2964-4101 sholeh.flam@gmail.com Shima Ghahari Shahid Bahonar University of Kerman, Kerman, Iran https://orcid.org/0000-0001-7182-8460 ghahary@uk.ac.ir Mohammad Abbas Nejad Shahid Bahonar University of Kerman, Kerman, Iran https://orcid.org/0000-0001-5287-0970 mabbasnejad2000@yahoo.com Abstract Cognitive organizers (COs) are text aids which represent objects, concepts, and their relations by the use of symbols and spatial arrangements without adding to semantic content. The present study examines language learners’ text comprehension through outlines, a popular CO, compared with text-only condition, and further investigates the effect of learner-constructed outlines (i.e., systematic note-taking) and expert-constructed outlines (i.e., readymade displays) on comprehension. Finally, the predictive power of multiple intelli- gences (MI) across different input modalities is scrutinized. Following strati- fied random sampling, a total of 111 EFL undergraduates were divided into text-only (receiving a text twice), expert-constructed (the text followed by an outline), and learner-constructed (the text followed by an outline to be drawn Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 360 up by the learner) groups. A TOEFL examination, a 1218-word expository text on systematic sleep disorder, a follow-up reading comprehension test, and a multiple intelligences inventory constituted the data collection measures. The results of multiple regression and ANOVA were as follows: (a) COs lead to more content re- call than text displays; (b) expert-constructed and learner-constructed outlines are equally effective; (c) MI significantly predicts the groups’ reading comprehension; (d) interpersonal and intrapersonal intelligences are significant correlates of text- only groups’ performance; and (e) visual, verbal, and intrapersonal intelligences are significantly associated with learner-constructed groups’ reading scores. The study offers several implications for theory and practice. Keywords: textual enhancement techniques; cognitive organizers; expert-constructed outlines; learner-constructed outlines; multiple intelligences; expository texts 1. Introduction As a predominant text genre in the present academic environments, expository (or scientific) texts are characterized by (a) the high density of unfamiliar and/or technical vocabularies, (b) the frequent use of causal and sequential text sche- mas, and (c) the need to integrate and draw numerous elaborative inferences with current segments of text (Diakidoy, Kendeou, & Ioannides, 2003). The ubiq- uitous presence of concepts and concept relations in expository texts calls for the implementation of techniques and/or strategies to render implicit connec- tions more explicit (van Gog, Kester, Nievelstein, Giesbers, & Paas, 2009). An approach that has been used over the past two decades to compen- sate for poor text structure (the other approach being text restructuring) is the use of cognitive organizers. Cognitive organizers (COs) or adjunct displays are broadly defined as text aids which represent objects, concepts, and their rela- tions by the use of symbols and their spatial arrangements without adding to the semantic content (McCrudden, Schraw, & Lehman, 2009). They hold great potential for helping readers see the unseen phenomenon by clearly and effi- ciently representing multiple intra- and inter-concept relations for the reader to view at a single glance (Amundsen, Weston, & McAlpine, 2008; Redford, Thiede, Wiley, & Griffin, 2012). According to Manoli and Papadopoulou (2012), COs dif- fer in the ways they depict the relations between concepts (e.g., vertical hierar- chical vs. nonlinear coordinate displays). A reader-friendly and easy-to-construct type of CO is an outline. Research on the effectiveness of COs, in general, and outlines, in particu- lar, on text comprehension has been inconclusive, with some investigations sug- gesting no significant difference between control and experimental groups and Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 361 others showing “significance for certain types of students when responding to certain types of questions” (Kinchin, 2014, p. 39). Despite second language (L2) learners’ more complex reading challenges as a result of their limited L2 com- petence and their higher demand for input enhancement techniques as supple- mentary aids, little research to date has studied the effectiveness of outlines for L2 learners (see below for the few exceptions). To bridge these gaps in the liter- ature, the present study investigates the contributions of two forms of COs, namely learner-constructed outlines (i.e., students’ systematic note-taking as a productive strategy) and expert-constructed outlines (i.e., students’ review of readymade outlines as a receptive strategy) in comparison with the text-only condition (presentation of a text twice), on L2 learners’ comprehension. It is worth mentioning that in this study, following the conventions in the literature, the terms adjunct displays, adjunct aids, concept maps, advance organizers, and cognitive organizers are used interchangeably, since outlines, as the focus of the study, belong to all the categories (for more on this see Tzeng, 2010). 2. Literature review In this section, initially, the most noticeable theories supporting the use of COs are introduced and described. Then, outlining, as a popular CO, will be presented by reviewing its different forms and advantages, the empirical studies into its impact on learning and comprehension, and potential research areas. Finally, the effect (or association) of individual differences, particularly cognitive and affective character- istics, with the use of COs will be addressed by reviewing relevant studies. 2.1. COs: Theoretical background A major concern of educational practitioners has long been to find a solution to the difficulties in comprehending the content (or expository) texts. Expository texts comprehension, as postulated by Robinson, involves “learning concepts [which] define attributes, recognizing defining attributes when presented with a range of examples, learning hierarchical and coordinate relations among con- cepts and finally, transferring this knowledge by correctly identifying concepts given new examples” (1998, p. 86). Some of the problems with comprehending these texts may be related to students and caused, for example, by their inability to draw inferences across sentences, lack of relevant content knowledge, or un- awareness of useful reading strategies. Other comprehension barriers can be attributed to the nature of the text and its poor organization or structure (Kendeou, van den Broek, Helder, & Karlsson, 2014; Schnotz, 2014). COs or adjunct displays (ADs) are among the strategies used for facilitating text comprehension. Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 362 COs can be simply defined as those supportive materials which include only im- portant text information and which differ in their formats and in the way(s) they communicate ideas. They are supposed to be abstract and inclusive, provide a means of organizing the new material, avoid distractions, save information pro- cessing resources, and enhance later recall and retrieval (Gurlitt & Renkl, 2010). There are several theoretical explanations in support of the adjunct display effect (ADE) (Darsh & Gersten, as cited in Robinson, Katamaya, & Fan, 1996). Ac- cording to the selective cued hypothesis (Mayer, 1984), the learning and recall ef- fects of COs are explained by the double presentation of the information, once in the text and once in the displays. Alternatively, the conjoint retention hypothesis (Kulhavy, White, Topp, Chan, & Adams, 1985) and dual coding theory (Paivio, 1983) maintain that “textual information referenced in a display is dually [conjointly] en- coded in memory, both verbally and spatially,” thereby leading to increased re- trieval effect (Marefat & Ghahari, 2009, p. 181). The third category of theories sup- porting ADE includes the visual argument (Waller, 1981) and computational effi- ciency (Larkin & Simon, 1987) hypotheses, which suggest that viewing objects in a two-dimensional position results in a quicker and easier computation of concept relations and facilitates later retrieval. Apart from being computationally efficient, COs are potentially search efficient. According to the search efficiency hypothesis (O’Donnell, 1993) and based on empirical research, COs are effective in locating information at both local (for scanning specific or local information) and global (for detecting the main idea) levels (Robinson & Skinner, 1996). 2.2. Expert- and learner-constructed outlines: Overview of existing research COs have been largely studied over the past two decades as a potential break- through in easing off the problems associated with text comprehension (Marefat & Ghahari, 2009). Examples include graphic organizers, concept maps, and out- lines of Robinson et al. (1996), knowledge maps with lists of Griffin and Robinson (2000), graphic organizers of Rowland-Bryant et al. (2009), and graphic overviews of Shaw, Nihalani, Mayrath, and Robinson (2012). The current literature provides evidence that outlines, as a type of CO, are favored over others (e.g., graphic organizers, knowledge maps, graphic over- views) for the following reasons: (a) they have a highly convenient and reader- friendly format, (b) they convey hierarchical concept relations, and (c) they are easy to design and construct (even by a layman; Robinson & Kiewra, 1995). In this study, the effectiveness of expert-constructed outlines (as an input-based receptive strategy) on reading comprehension was compared with learners’ self- generated outlines (as an output-based and productive strategy). Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 363 Expert-constructed outlines enjoy a number of advantages: (a) they con- tain the most salient ideas of the text, which are most likely to be included in assessment measures too, (b) the ideas are organized in a logical sequence (i.e., superordinate ideas are followed by the subordinates), (c) they help students grasp the content better through a simplified presentation of the text, (d) they may assist instructors at identifying subtle nuances of certain contents and de- tect possible areas of difficulty prior to teaching, and (e) they can be interjected at different parts of a text without requiring extensive student training or taking much class time (McCagg & Dansereau, 1991). On the other hand, Boyle and Weishaar (1997) enumerate four advantages of having students generate their own outlines. First, students gain a better understanding of the main points of the material and relations between them when constructing their own displays. Second, students can personalize the outlines by using their own terms, abbre- viations, and symbols. Third, once trained, students can construct them with similar content in other classes. Finally, students get more actively and autono- mously involved in an activity (e.g., reading assignment or lecture) when they develop outlines on their own, as opposed to reviewing a readymade display. The literature on the effect of adjunct aids on students’ text comprehen- sion, however, is limited, context-specific (e.g., students with learning disabili- ties), and inconclusive (Kinchin, 2014; Manoli & Papadopoulou, 2012; Stull & Mayer, 2007). Even fewer studies have researched the cross-linguistic dynamics of the COs and their effectiveness in L2 learning contexts. Through a pre-/post- test design study, Chularut and DeBacker (2004) scrutinized the possible facili- tative effect of concept mapping on ESL students’ (N = 79) learning from English texts. The results revealed that students’ language achievement as well as learn- ing self-regulation and self-efficacy improved as a result of studying English-lan- guage texts accompanied by COs. Suzuki, Sato, and Awazu (2008) also investi- gated the instructional effectiveness of the spatial graphic representation of an English sentence with coordinators in EFL reading settings. They used two dif- ferent types of displays (a linear sentential representation and a spatial graphic representation) and studied 56 first-year undergraduates as participants. The results indicated that the readers comprehended graphic representation of texts significantly better and more effectively than sentential displays. Having conducted a comparative study on two types of expert-con- structed displays (i.e., outlines and graphic organizers), Marefat and Ghahari (2009) observed that adjunct aids were more efficient than text aids for reading comprehension of L2 readers (71 undergraduates). However, multiple-choice reading tests revealed that neither of the displays was superior to the other. Similarly, Rahmani and Sadeghi (2011) examined the product and process ef- fects of two expert-constructed aids, namely note-taking instruction and graphic Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 364 organizers, on the comprehension and retention of L2 written input. The results revealed that students who completed and studied graphic organizers per- formed considerably better in both comprehension and recall conditions than did students who studied their conventional outlines. That is, both the product and process effects of note-taking instruction were approved. Despite ample evidence in support of the effectiveness of COs, “there are some studies that yield conflicting results regarding [their] use” (Manoli & Papadopoulou, 2012, p. 353). For instance, Alvermann (1981) evaluated the compensatory effect of graphic organizers on descriptive texts. Participants (114 tenth graders) were required to read two versions of an expository passage (comparison versus description) and a graphic organizer. Immediate and delayed recall measures suggested that the exper- imental group outperformed the control group under the descriptive text condition. Results indicated that graphic organizers were useful for reorganization of infor- mation but ineffective when the reorganization was unnecessary. Bean, Singer, Sorter, and Frazee (1986) compared the effectiveness of graphic organizers and outlining for students in 10th-grade world history classes. The participants were randomly as- signed to one of the three groups (graphic organizer with previous training in summa- rization, graphic organizer alone, and outlining). No differences were detected be- tween graphic organizers, outlines, and traditional instruction for comprehension and recall of text information. Balajthy and Weisberg (1990) and Davis (1994) were also among the studies which found that COs were effective for certain groups rather than for all learners, that is to say, for low ability and beginning level students. Rice (1994) and Griffin and Tulbert (1995) questioned the “facilitative effects of graphic organizers on text comprehension” (as cited in Manoli & Papadopoulou, 2012, p. 353). Likewise, Kools, van de Wiel, Ruiter, Crüts, and Kok (2006) examined the effect of graphic or- ganizers on the comprehension of a health education brochure text and compared subjective and objective comprehension measures. Participants were asked to read a brochure text about asthma with and without these organizers, and subjective and objective measures of text comprehension were administered. Findings suggested that, in contrast to the effects of graphic organizers on objective text comprehension, there was no difference between the groups on the subjective measures of compre- hension (i.e., open-ended comprehension questions). Finally, Ciullo and Reutebuch’s (2013) summary of 12 studies into the effect of graphic organizers or concept maps for students with learning disabilities suggested that mapping was not effective for improving learning unless the instruction was explicit. 2.3. COs and individual differences Research has suggested that the beneficial effects of COs are mediated by learners’ individual characteristics, namely cognitive and affective variables. Basque and Lavoie Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 365 (2006), in their overview of the studies into the effectiveness of collaborative concept maps, found that success in the use of COs depends to a large extent on learner char- acteristics such as motivation and situational factors like the mode of learning. They documented that COs are most effective for highly motivated learners and in face-to- face learning situations. There is also evidence that, similar to most learning strate- gies, students with low verbal ability benefit more from COs-supported materials than do high-ability learners (Manoli & Papadopoulou, 2012). As Nesbit and Adesope ascertain, the structural form of COs, “specifically the use of brief labels and simple node-link-node syntax to represent propositions, may be more easily comprehended and constructed by learners who have lower verbal ability” (2006, p. 420). Besides, COs have been more efficient for the students with low prior knowledge than those with high background knowledge. Comparing the effects of three types of aids (i.e., knowledge maps, outlines, and lists) on students’ recall of college-level biology lectures, Lambiotte and Dansereau (1992) revealed that knowledge maps were more effective than the other two aids for the students with low prior knowledge of biology. They reasoned that “the specific macrostructure signaled by [them] might guide the knowledge construction of less knowledgeable students but conflict with the cognitive structures already established in more knowledgeable students” (as cited in Nesbit & Adesope, 2006, p. 420). The litera- ture also supports the association between students’ self-regulation and self-effi- cacy competencies with their effective use of COs (Chularut & DeBacker, 2004). According to Gardner (1983), multiple intelligence theory (MIT) is a learner- centered theory that considers learners as different individuals possessing varying types of intelligences and learning dispositions. Accordingly, learners with differ- ent intelligence types come across a problem-solving task (like an L2 reading com- prehension assignment) with different sets of strategies. Gardner defined multi- ple intelligence as “the ability to solve problems, or to create products, that are valued within one or more cultural settings” (1983, p. 81). There are at least nine ways that people have of comprehending and realizing the world. Table 1 sum- marizes the definitions of these nine micro-intelligences. Table 1 MI and its subscales Micro-intelligence Definition Verbal intelligence The ability to produce and perceive language in oral and written forms effectively Logical intelligence The effective use of numbers and reasoning in problem solving tasks Visual intelligence The graphical ability to use visual things and ideas in space, color, form, and shape Kinesthetic intelligence The effective use of whole or parts of body to solve problems Musical intelligence The sensitivity to rhythm, pitch, and melody to express emotions and thoughts Naturalist intelligence The capacity to perceive and classify the natural world and environment Existential intelligence The philosophical ability to tackle deep questions about life and human existence Intrapersonal intelligence The ability to recognize and accept one’s capabilities and limitations Interpersonal intelligence The ability to manage one’s relationships and interactions with others Notes. verbal = linguistic; logical = mathematical; kinesthetic = bodily; visual = spatial. Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 366 Based on an extensive literature review, MI is a significant determiner and/or correlate of a variety of learning mechanisms and outcomes; among them are learning strategies awareness and use (Akbari & Hosseini, 2008), learn- ing styles (Denig, 2004; Vincent & Ross, 2001), knowledge retention and recall (Ozdemir, Guneysu, & Tekkaya, 2006), literacy skills (Brand, 2006), reading achievement (Armstrong, 2003; McMahon, Rose, & Parks, 2004), writing profi- ciency (Looi & Mustapha, 2010; Saricaoglu & Arikan, 2009), and learners’ beliefs and attitudes (Bas & Beyhan, 2010). Given the fact that COs are among the pop- ular learning strategies, it was presumed in this study that their application may be mediated by learners’ MI, too. Such an association, however, has not yet been investigated. For this reason, MI is studied here as a potential moderator for text comprehension across three input modalities. 3. Aims of the study Notwithstanding the pressing demands of language learning settings for versatile input enhancement techniques and despite language learners’ more complex reading challenges as a result of limited L2 competence, little research to date has investigated the effectiveness of expert- and learner-constructed adjunct aids in this certain context. As Manoli and Papadopoulou contend, “allowing for the non- supportive findings of studies, room for research is left in further exploring the effectiveness of [COs] as a reading strategy, especially in the language teaching courses” (2012, p. 354). In addition, there has been no attempt to examine the mediating effect of multiple intelligences on the optimal use of COs. The present study is guided by four motivations: (a) the high proportion of expository texts in academia and their comprehension complexity, (b) the limited language competency of some L2 readers, which compounds their comprehen- sion difficulties, (c) the scant and inconsistent literature on outlines, as a leading input enhancement technique and CO, in L2 reading contexts, and (d) the absence of empirical research into the mediatory role of multiple intelligence on the effi- ciency of COs, in general, and outlines, as a particular subcategory of them. The following research questions were addressed in the present study: 1. Is there any significant difference between the effect of text displays and outline displays on L2 readers’ text comprehension? 2. Is there any significant difference between the effects of expert- and learner-constructed outlines on L2 readers’ text comprehension? 3. Does L2 learners’ multiple intelligence predict their text comprehension across the input modalities? Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 367 4. Methodology The research features a descriptive case study and adopts an ex-post facto de- sign for it examines the effect of a single treatment across several groups. In the first part, input enhancement with three levels of text-only (no advance organ- izer), learner-constructed outlines, and expert-constructed outlines served as the independent variable and text comprehension was the dependent variable. In the next stage of data coding, the independent variable (or predictor) was multiple intelligence with its nine subscales and the dependent variable was text comprehension across the three modalities. 4.1. Participants A total of 120 students (aged from 18 to 30, M = 21.30) from six different classes took part in the current study for some course credit. They were all junior stu- dents (80 females and 40 males) majoring in English literature and translation at two state-run universities in the southeast of Iran. Therefore, respondents in this study were homogenized in terms of their first language, field of study, ex- perience with expository texts structures, and reading practices. A convenience sampling technique was employed by administering the tests to six classes the instructors and students of which agreed to cooperate. The English learners in the present study live in a typical foreign language envi- ronment and, like many Asian L2 English learners, do not have sufficient expo- sure to the target language; therefore, they tend to receive a good portion of their L2 input from reading (Ghahari & Ahmadinejad, 2016a, 2016b; Ghahari & Basanjideh, 2015, 2017; Ghahari & Heidarolad, 2015). After coding and scoring the data, nine of the participants were excluded because their answer sheets were filled either incompletely or inaccurately. As a result, a total of 111 data sheets remained for further analyses. The English proficiency level of the sample was examined via a TOEFL ex- amination (Educational Testing Service, 2004). A one-way ANOVA revealed no significant difference between the three groups, suggesting that the sample’s proficiency level was homogeneous and, considering their average scores, was the (upper)intermediate level (see Table 2). Table 2 Sample composition and proficiency check results Group Mean SD F Sig. Text-only (n = 36) 20.42 6.15 1.322 .271 Outline (n = 35) 21.97 5.96 Learner-constructed (n = 40) 22.50 5.14 Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 368 Thus, level of proficiency, field of study, age, L1 background, educational level, and nationality were controlled, but learners’ individual differences like gender, learning styles, and study habits were possible confounding variables. 4.2. Materials The study involved three instruments: (a) a TOEFL examination (ETS, 2004), (b) the CO package (including a text, an outline, and a multiple-choice test) (Katayama & Robinson, 2000), and (c) the multiple intelligence inventory (McKenzie, 2005). Each instrument is described in detail below. 4.2.1. The proficiency test The TOEFL used in this study was one of the six full-length paper-based tests administered by ETS (2004). The test, which aimed at determining the subjects’ language proficiency, contained a total of 40 questions including structure, writ- ten expression, and reading comprehension subtests. The whole test lasted 40 minutes to complete. Using a Cronbach’s alpha formula, the reliability was esti- mated to be .73, which is acceptable according to Cohen’s (as cited in George & Mallery, 2003) criteria. 4.2.2. COs package: The original draft The original package of CO was designed by Katayama and Robinson (2000). The criteria for this selection were two-fold: (a) the materials were already devel- oped and validated by a panel of experts in the field, and (b) they were closely relevant to our objectives in this study. In their research, the variable under study was text length; therefore, they provided their subjects with a chapter- length expository text covering the topic of sleep disorders. As stipulated earlier, a text is characterized as expository if it encompasses numerous unfamiliar and technical terms, a causal and sequential text structure, and multiple intercon- nected concepts to be elaborately inferred (Diakidoy et al., 2003). Following these criteria, Katayama and Robinson (2000) selected a text which addressed six spe- cific types of sleep disorder. It contained approximately 3,500 words (with nearly 1,500 technical terms) and was distributed on eight single-spaced pages. The text was followed by a 30-item, four-option multiple-choice test measuring the factual knowledge of information explicitly stated in the text (i.e., display items). The reason for the inclusion of factual questions was to minimize the intervening effect of mental processes since display and inferential items call for different information processing paths: Inferencing refers to “the abstraction Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 369 of information that is not explicitly presented” and is a non-linear and multifac- eted ability, where more than single information should be effectively compre- hended, restored, and retrieved at the time of task completion (Botting & Ad- ams, 2005, p. 50). Display items, on the other hand, require learners to readily and accurately recall text information in a linear manner. Hence, in answering display items, intensive reading and linguistic knowledge are the responsible pa- rameters, whereas answering inferential items needs a strategic approach (an awareness of cognitive and metacognitive strategies) towards a text (Jaswal & Markman, 2001). Katayama and Robinson (2000) also administered a 10-item matching test of application to assess the students’ ability to apply knowledge from the text to novel examples. 4.2.3. COs package: The modified draft The materials used in Katayama and Robinson’s (2000) study were modified by Marefat and Ghahari (2009) to adjust to the limitations of class time, students’ tolerance, and their research objective. They divided the original text, which was a complete chapter on different types of sleep disorder, into three texts each cov- ering one type of sleep disorder. The COs were the same as the original version with regard to their type and number. They did not make any changes in the num- ber and format of the test items either. The instruments were in three sets: Each set included a text, an outline, a graphic organizer, and a test consisting of 10 four- option multiple-choice factual items. The number of words ranged from an ap- proximate of 600 to 1,000, typed on single-spaced pages. The package was piloted before the main study and the test reliability was computed (α = .76). For the purpose of this study, one set of materials used in Marefat and Ghahari’s (2009) research was chosen and used iteratively. This set consisted of a 1,218-word text focusing on one type of sleep disorder (i.e., systemic sleep disorder), an outline of the same text (i.e., the expert-constructed display), and a test consisting of 10 four-option multiple-choice display items. The internal consistency of the test was found to be acceptable (α = .71). 4.2.4. The multiple intelligence checklist The multiple intelligence (MI) test designed by McKenzie (2005) was employed in this study. It consists of 9 sections each containing 10 questions. In the order of appearance, the sections reflected the participants’ naturalistic, musical, log- ical, existential, interpersonal, kinesthetic, verbal, interpersonal, and visual strengths. The reliability of the test fell within the acceptable range (a = .78). Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 370 4.3. Procedure The data collection procedure was completed over the period of two months (from early May through to late June 2015) in six academic classes. The partici- pants gave their informed consent to take part in the study and were assured that their anonymity was strictly protected. To control for the effect of back- ground knowledge, the text topic was disclosed to the participants prior to the study and their familiarity with it was inquired. They all admitted that the topic was novel and fairly unknown to them. The instruments were administered over two sessions (90 min) outside of the regular class time. Using stratified random sampling, each class was divided into three groups. The study was carried out differently in the three groups, namely expert- constructed display, learner-constructed display, and text-only display groups. However, activities like taking the TOEFL, completing the MI test, studying the expository text, answering the follow-up reading comprehension test, as well as the time allotted to each task were common across them. Below is the full de- scription of the procedure in each group. 4.3.1. Expert-constructed groups The groups received the text and were given 10 minutes to study it. They were notified that the text would be collected before they received the comprehen- sion test and that it was a text-for-test task requiring a detailed study. Having returned the texts, the participants received the outline of the same text. They were briefly notified that the outline was based on the same text and would help them answer the follow-up questions. Ten minutes were allotted for the study of the displays. The added materials were then collected and the students started the testing part of the experiment which included 10 multiple-choice questions (10 min). After submitting the test, they were asked to fill out the MI survey checklist. 4.3.2. Learner-constructed groups A week before the experiment, the researcher practiced over the course of a 90- minute session with the students how to develop a standard outline. The pro- cedure in this group is consistent with the guidelines suggested by Haugwitz, Nesbit, and Sandmann (2010) and Schroeder, Nesbit, Anguiano, & Adesope (2018). At the end of the practicum, most of the students’ notes were in the shape of standard outlines. Thus, they were partly familiar with the construction and organization of outlines and no confusion and questions were raised during Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 371 the main study. In the treatment session, the students received the text and were given 10 minutes to read it. They were asked to review it carefully and were notified that the text would be collected before test administration. Having submitted the texts, the participants were asked to develop an outline out of it. They were given 10 minutes to do the task. The constructed materials were then collected and the participants started doing the multiple- choice comprehension test (10 min). After completing the test, the students went through the MI checklist. 4.3.3. Text-only groups The text-only groups received the same text and reviewed it over 10 minutes. They were notified that they had to read it carefully and return it before test administration. The groups were then offered another 10 minutes to study the text for the second time. Next was the testing part in which the subjects, like the expert- and learner-constructed groups, sat for the multiple-choice compre- hension test (10 min) and the MI checklist. 4.4. Data analysis For the effect of input enhancement type on text comprehension, a t test and a one- way ANOVA with a follow-up post hoc Scheffe test were used. To examine the predic- tive power of multiple intelligence (with nine layers) in relation to reading compre- hension (under the three conditions), a multiple regression analysis was run. 5. Results As depicted in Table 3, the expert-constructed groups achieved the highest mean score (M = 6.86, SD = 2.14) followed by the learner-constructed condition, which stood at the second place (M = 6.35, SD = 1.72). The lowest mean score in the com- prehension test was achieved by the text-only group (M = 5.61, SD = 2.17). Table 3 Descriptive statistics for the input groups’ reading comprehension (N = 111) Groups Min Max Mean (SD) Text-only (n = 36) 2 9 5.61 (2.17) Expert-constructed concept map (n = 35) 2 9 6.86 (2.14) Learner-constructed concept map (n = 40) 3 10 6.35 (1.72) In order to examine whether there is any significant difference between the effect of COs (i.e., expert- and learner-constructed groups) and the text-only Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 372 condition on L2 learners’ text comprehension, an independent samples t test was run. Preliminary Levene’s test confirmed the equality of variance (F = .116, p = .73). It was revealed that the outline groups significantly outperformed the text- only groups, implying that the provision of outline as a textual enhancement tech- nique successfully enhanced reading achievement (t = -2.43, df = 69, p = .018). In order to get a clearer picture of the effect of outlines and to allow for a cross-comparison, a one-way ANOVA was run for the three groups. As Table 4 demonstrates, the ANOVA result was significant (F = 3.46, p = .035) and the ef- fect size was moderate (h2 = .06) following Cohen’s (1988) criteria. It implies, therefore, that there is a significant difference among the given input modes. Table 4 ANOVA results for the three input modes Sum of squares df F h2 Between groups 27.951 2 3.462* .06 Within groups 435.941 108 Total 463.892 110 Notes. * p < .05. In order to specifically address the second question and to find out the most effective outline presentation mode, a post-hoc Scheffe test was run. Ac- cording to Table 5, the learner-constructed and expert-constructed conditions did not significantly differ in terms of their effectiveness on text comprehension (p = .554). When compared in pairs, then, the only significant difference in Table 5 lies between the expert-constructed and text-only groups (p = .037). Table 5 Post-hoc comparisons among the three input modalities Group Mean difference Std. error Sig. TO vs. LC -.739 .462 .282 TO vs. EC -1.246 .477 .037 LC vs. EC -.507 .465 .554 Notes. TO = text-only; LC = learner-constructed; EC = expert-constructed. To sum up, outlines in general were effective for expository texts compre- hension compared with presenting a text twice; there existed, however, no dif- ference between the two modes of input-based (expert-constructed) and out- put-based (learner-constructed) displays, to use Van Patten’s (1996) term. Finally, to test the prediction power of multiple intelligences in relation to text comprehension across the input modes, a multiple regression analysis was run, the results of which are as follows. As Table 6 suggests, text-only (F = 1.11, r2 = .27, p < .05) and learner-constructed (F = 2.54, r2 = .43, p < .01) groups’ performance could be predicted by MI. Of the multiple intelligence subscales, Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 373 interpersonal (t = 2.28, p < .01) and intrapersonal (t = 2.17, p < .01) intelligences were significant predictors of text-only groups’ performance; that is to say, those with a higher level of interpersonal and intrapersonal intelligences outper- formed the text-only condition. Table 6 Correlational and regressional results with input modality as criterion variable (N = 111) Predictor (intelligence type) Text-only EC LC R Beta T R Beta t R Beta t Naturalistic -.02 -.31 -1.48 -20 .22 .88 -.15 .00 .01 Musical .03 .39 1.70 .04 .18 .80 -.05 -.32 -1.90 Logical -.11 -.38 -1.80 -25 -.08 -.30 -.10 -.18 -1.07 Existential .13 -.14 -.69 .26 -.11 -.54 .17 -.04 -.30 Interpersonal .22 .47 2.28* -13 -.03 -.14 .07 -.01 -.07 Kinesthetic .05 .14 .64 -42 -.02 -.10 -.00 .34 1.83 Verbal -.07 -.49 -1.99 -15 -.09 -.36 .03 .61 2.84** Intrapersonal .13 .54 2.17* -05 -.09 -.31 .16 .50 2.62* Visual .11 .10 .54 .18 .02 .075 .24 -.62 - 3.17** F R2 F R2 F R2 1.11* .27 .20 .06 2.54* .43 Notes. EC = expert-constructed; LC = learner-constructed; * p < .05; ** p < .01. With respect to the learner-constructed condition, verbal (t = 2.84, p < .01) and visual intelligences (t = -3.17, p < .01) were found to be the strongest predictors of group performance, followed by intrapersonal intelligence (t = 2.62, p < .05). No other significant interaction was detected among the MI sub- scales and the three input modes. 6. Discussion Three research questions were investigated in this study. First, we asked whether adjunct displays lead to better text comprehension than text displays do, as well as which text enhancement technique (input-based vs. output- based) is more suitable for L2 learners’ text comprehension. The analysis showed that adjunct aids (outlines) were more efficient than texts as they pro- duced significantly higher scores on comprehension than texts did. Our findings provide evidence in support of ADE (i.e., adjunct displays effect) and are con- sistent with the results of previous studies (e.g., Amundsen et al., 2008; Marefat & Ghahari, 2009; Jiang & Grabe, 2007; Rowland-Bryant et al., 2009; Schroeder et al., 2018; Shaw et al., 2012), affirming that when text is accompanied by ad- junct aids, comprehension of text information is improved. Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 374 There are several justifications for the better performance of the outline groups over the text-only group. Firstly, as maintained by Krug, George, Hannon, and Glover (1989), outlines can contribute to decoding a passage by activating both form schemata (i.e., keywords) and context schemata (i.e., main ideas). An alternative explanation is related to the form of presentation: An outline presents topics and subtopics in a hierarchical form and sequences the concepts and their relationships from the most general through to the most specific. This hierarchical organization and connection of prior knowledge to the new information matches the knowledge structure in the brain and, therefore, results in meaningful learn- ing (Marefat & Ghahari, 2009). Another plausible rationale for the contribution of outlines to text comprehension may refer to their structure, in that they are more computationally effective and search-efficient (both locally and globally) than a plain text. As Redford et al. (2012) maintain, they increase the salience of the cues, lessen the working memory requirements, and provide more resources for text comprehension. This is in line with the major tenets of search efficiency, conjoint retention, dual coding, visual argument, and computational efficiency hypotheses, all of which suggest that the contribution of outlines to searching and locating information (local and global) lies in their physical structure. According to McCrud- den et al. (2009), outlines (as a CO) promote text comprehension and recall by minimizing the cognitive load needed to get the intended message and activating relevant background knowledge (i.e., schemata). This reasoning is also in con- formity with cognitive load theory (Sweller, Van Merrienboer, & Pass, 1998), and meaningful learning hypothesis (Ausubel, 1963), which reckon an optimal level of information load and input quality as a key to learning and retrieval. Comparing outlines with text displays, however, provides counterevi- dence to selective cued hypothesis (Mayer, 1984). According to the hypothesis, better recall of information induced by the displays pertains, more than any- thing else, to the presentation of the information twice, once in the text and once in the displays. However, as it was indicated earlier, the text-only groups received the same text twice but still underperformed in the comprehension test in comparison to the outline groups. Finally, and more specifically related to language learning contexts, Schmidt’s (1990) noticing hypothesis warrants discussion. According to the hypothesis, for any kind of learning and recall to happen, learners have to consciously attend to the target features in the input. It can be rationalized that by inserting appropriate displays in the texts, teachers and materials developers can direct learners’ attention to certain points (usually the main ones) and maximize their learning outcome. The second research question was whether the type of display the stu- dents viewed (expert- vs. learner-constructed) would differentially affect their performance on the comprehension test. No significant difference was observed Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 375 between the expert- and learner-constructed groups. According to Kiewra (1985), note-taking can facilitate learning by boosting attention, raising awareness of text or- ganization, storing the information into memory, and encouraging the learner to com- pare the material with previously learned, which is known as the encoding hypothe- sis. The fact that no significant difference was detected between the two display types in this study is in contradiction to the results of Schroeder et al. (2018), Kiewra (1985), and Katayama and Robinson (2000) in L1 settings and Rahmani and Sadeghi (2011) in L2 reading contexts. One justification for this contradictory finding can be the review- ing factor. According to Crooks, White, and Barnard (2007), the value of note-taking lies in its two salient properties: as a technique that scales up encoding of the content (i.e., encoding hypothesis) and as a device for externally storing the material (i.e., ex- ternal storage idea). The external storage hypothesis postulates that “note-taking per se is not facilitative of recall, unless learners are given the opportunity to review their notes prior to recall” (Rickards & Friedman, 1978, p. 136). Rahmani and Sadeghi (2011) also maintain that notes serve as a storage device of information that can assist in retrieving the content in delayed recalls and in answering exam questions provided that they are systematically reviewed. As little time was invested and/or remained for the learner-constructed groups in this study to review the notes, its comparable per- formance to the expert-constructed groups does not seem unexpected. The final research question was related to whether learners’ multiple in- telligences predicted their performance on different types of textual presenta- tion. Results revealed that from among the intelligence types under study, inter- personal and intrapersonal intelligences significantly predicted the text-only groups’ performance, while visual, verbal, and intrapersonal intelligences were significant predictors of the learner-constructed groups’ reading scores. The for- mer can be accounted for on several grounds: Interpersonal intelligence, as de- fined by Nicholson-Nelson (1998), refers to the ability to work effectively with other people and to understand them and recognize their goals, motivations, and intentions. Students who exhibit a high endowment of this intelligence have strong leadership skills and are skilled at organizing, communicating, mediating, and negotiating. According to Gardner (1983), an individual who is high in inter- personal intelligence understands the intentions, motivations, needs, and de- sires of others better, and is capable of working effectively with them. Therefore, it may be inferred that a reader who inherently has a higher level of interpersonal intelligence can make sense of the text and deduce the author’s intention more readily and successfully. Similarly, intrapersonal intelligence has been described as the ability to understand oneself, to assess one’s strengths and weaknesses, and to act effectively using this knowledge source (Gardner, 1983). Students gifted in intrapersonal ability have a strong sense of self, are confident, and can enjoy working alone. They naturally notice and acknowledge their potentials and Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 376 identify ways of circumventing challenges more efficiently. This reasoning might explain why intrapersonally intelligent students turned out to be more successful in doing text-only assignments, which are by their nature more demanding and reader-unfriendlier than the competing ones. It must be noted that, in order of difficulty, the text-only condition followed by the learner-constructed mode de- manded more attention and commitment on the part of the learners. In the ex- pert-constructed condition, however, the tasks were ready-made and scaffolded and, therefore, put little burden of responsibility on the readers’ shoulders. The next MI-related finding was the mediating role of visual, verbal, and in- trapersonal intelligences in relation to the learner-constructed groups’ text perfor- mance. Visual (or spatial) intelligence (intelligence of pictures and images) is de- fined by Nicholson-Nelson (1998) as the ability to create spatial representations of the world and to transfer them mentally or concretely. Students who are endowed with a high level of spatial intelligence tend to understand new information more productively if it is accompanied by a mental or physical picture; they do well with maps, charts, and diagrams, favor mazes and puzzles over plain texts, and are skilled at drawing, designing, and creating things. Accordingly, a student with high vis- ual/spatial intelligence benefits more than the competing peers from COs like out- lines, which simplify the flow of information, logical arguments, explanations, and examples present in a typical expository text. Another predictor of learner-con- structed groups’ performance was verbal intelligence. Gardner (1983) has de- scribed verbal (or linguistic) intelligence as one’s sensitivity to spoken and written language, ability to use language to accomplish goals, as well as ability to learn new languages. Based on this definition, students who exhibit verbal/linguistic intelli- gence have a preference for writing, reading, telling stories, and solving puzzles. Ac- cordingly, they learn best through hearing and seeing words, speaking, writing, and reading. Learner-constructed outline mode matches these students’ writing and note-taking abilities, which in turn will result in a better test performance. 7. Conclusion and implications To recap, three plausible conclusions are drawn on the basis of the findings: (a) learner- and expert-constructed outlines are more effective than text-only con- dition for L2 text comprehension; (b) students with higher verbal and visual competencies are more successful in taking systematic notes and organizing them into outlines, a task which calls for both language and spatial competencies; (c) those with a high emotional intelligence1 (i.e., intrapersonal and interpersonal) 1 Emotional intelligence (EI) refers to the capacity to recognize one’s and others’ emotions and to manage one’s relationships and interactions with others. According to Goleman (1998), EI ac- tually encompasses intrapersonal and interpersonal components of multiple intelligences. Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 377 competency are more active and self-regulated learners when assigned de- manding and intricate tasks to accomplish. Based on the above observations, the following implications for practice are suggested: 1. The study gives credence to the role of input enhancement techniques, supporting the idea that with these instructional interventions the amount of time spent on reading a text and the amount of cognitive ca- pacity allotted to its processing are considerably lessened. Educators and materials developers are encouraged to incorporate outlines to help readers, particularly L2 learners, learn more inter-concept relations and text structure and to improve text comprehension and recall. Outlines can be utilized for both learning and assessment purposes. They can be incorporated as warm-up, brainstorming, preview, and review activities. 2. It is recommended that teachers instruct students on different forms of note-taking (conventional and systematic) practices. By training students to construct outlines while reading, they will not only learn the target ma- terials but also learn how to learn. However, students must be given time to review their self-designed notes or outlines for more effective results. 3. Outline practices are better viewed as a developmental and graded ac- tivity. That is to say, practicing and interpreting expert-constructed out- lines are more suitable for novice readers since they typically help max- imize feelings of encouragement and motivation. On the other hand, outline construction is more suitable for later stages to foster learner autonomy and self-regulation. 4. The predictive power of multiple intelligence in relation to input modal- ities of text presentation offers insights for teachers and educators to take cognitive and affective styles of the learners into account. As Leyu (2001) and Ghahari and Sedaghat (2018) contend, the number of in- structional decisions in education will be markedly increased by taking learners’ individual differences and preferences into account. Hence, the role of the teachers as the most influential agents that can promote the one-method-does-not-fit-all approach is highlighted. It is recommended that teachers triangulate a variety of strategies and techniques to ad- dress both the educational and psychological needs of L2 readers. Other research avenues also exist. First, from among the textual enhancement techniques, only outlines (learner- and expert-constructed modes) were studied here. Thus, one area for further investigation is comparing outlines with other COs (e.g., graphic organizers, underlining, and mnemonics). Second, this study was limited to expository texts and cross-sectional data collection. Future studies Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 378 could investigate the long-term retention effect of outlines, apply a longer treat- ment, incorporate follow-up review assignments, and examine their effective- ness for other text genres (e.g., narrative and argumentative). Finally, a larger sample size could be included in future studies in order to maximize the gener- alizability of the findings. Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 379 References Akbari, R., & Hosseini, K. (2008). Multiple intelligences and language learning strategies: Investigating possible relations. System, 36(2), 141-155. Alvermann, D. (1981). The compensatory effect of graphic organizers on descrip- tive text. The Journal of Educational Research, 75, 44-48. Amundsen, C., Weston, C., & McAlpine, L. (2008). Concept mapping to support university academics’ analysis of course content. Studies in Higher Educa- tion, 33(6), 633-652. Armstrong, T. (2003). The multiple intelligences of reading and writing: Making the words come alive. Alexandria: Association for Supervision and Curric- ulum Development. Ausubel, D. (1963). The psychology of meaningful verbal learning. New York: Grune and Stratton. Balajthy, E., & Weisberg, R. (1990, December). Effects of reading ability, prior knowledge, topic interest, and locus of control on at-risk college students’ use of graphic organizers and summarizing. Paper presented at the annual meeting of the National Reading Conference, Miami, FL. https://www.semantic scholar.org/paper/Effects-of-Reading-Ability%2C-Prior-Knowledge%2C-To pic-BalajthyWeisberg/385fbfd36ebb8a34aa19541ffb0cbe 7fb80f79d0 Basque, J., & Lavoie, M. C. (2006). Collaborative concept mapping in education: Major research trends. In A. J. Cañas & J. D. Novak (Eds.), Concept maps: Theory, methodology, technology: Proceedings of the Second Interna- tional Conference on Concept Mapping (pp. 79-86). San Jose, Costa Rica. Bas, G., & Beyhan, O. (2010). Effects of multiple intelligences supported project-based learning on students’ achievement levels and attitudes towards English lesson. International Electronic Journal of Elementary Education, 2(3), 365-386. Bean, T., Singer, H., Sorter, J., & Frazee, C. (1986). The effect of metacognitive instruction in outlining and graphic organizer construction on students’ comprehension in a tenth-grade world history class. Journal of Reading Behavior, 18, 153-169. Botting, N., & Adams, C. (2005). Semantic and inferencing abilities in children with communication disorders. International Journal of Language & Com- munication Disorders, 40(1), 49-66. Boyle, J., & Weishaar, M. (1997). The effects of expert-generated versus student-gen- erated cognitive organizers on the reading comprehension of students with learning disabilities. Learning Disabilities Research & Practice, 12(4), 228-235. Brand, S. (2006). Facilitating emergent literacy skills: A literature-based, multiple intelli- gence approach. Journal of Research in Childhood Education, 21(2), 133-148. Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 380 Chularut, P. & DeBacker, T. (2004). The influence of concept mapping on achieve- ment, self-regulation, and self-efficacy in students of English as a second language. Contemporary Educational Psychology, 29, 248-263. Ciullo, S., & Reutebuch, C. (2013). Computer-based graphic organizers for stu- dents with LD: A systematic review of literature. Learning Disabilities Re- search & Practice, 28, 196-210. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum. Crooks, S., White, D., & Barnard, L. (2007). Factors influencing the effectiveness of note taking on computer-based graphic organizers. Journal of Educa- tional Computing Research, 37(4), 369-391. Davis, Z. (1994). Effects of prereading story mapping on elementary readers’ comprehension. Journal of Educational Research, 87, 353-360. Denig, S. (2004). Multiple intelligences and learning styles: Two complementary dimensions. Teachers College Record, 106(1), 96-111. Diakidoy, I., Kendeou, P., & Ioannides, C. (2003). Reading about energy: The ef- fects of text structure in science learning and conceptual change. Contem- porary Educational Psychology, 28(3), 335-356. Educational Testing Service (2004). Test and score data summary. 2003-04 test year data: Test of English as a foreign language. https://www.ets.org/Media/ Research/pdf/TOEFL-SUM-0304.pdf Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. New York: Basic Books. George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. Boston: Allyn & Bacon. Ghahari, S., & Ahmadinejad, S. (2016a). Operationalization of Bachman’s model via a multimodal reading comprehension test: Screening test method facets and testees’ characteristics. Studies in Educational Evaluation, 51, 67-76. Ghahari, S., & Ahmadinejad, S. (2016b). Performance on a triangulated reading test battery: A study of language learners’ individual differences and ret- rospective perceptions. Psychological Studies, 61(3), 245-258. Ghahari, S., & Basanjideh, M. (2015). Dynamics of strategies-based language in- struction: A study of reading comprehension and problem solving abilities via structural equation modeling. RELC Journal, 46(3), 237-253. Ghahari, S., & Basanjideh, M. (2017). Psycho-linguistic model of reading strate- gies awareness in EFL contexts. Reading Psychology, 38(2), 125-153. Ghahari, S. & Heidarolad, M. (2015). Multiple-choice glosses and incidental vo- cabulary learning: A case of an EFL context. Reading Matrix 15(1), 262-273. Ghahari, S., & Sedaghat, M. (2018). Optimal feedback structure and interactional pattern in formative peer practices: Students’ beliefs. System, 74(3), 9-20. Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 381 Goleman, D. (1998). Working with emotional intelligence. New York, NY: Bantam Books. Griffin, C., & Tulbert, B. (1995). The effect of graphic organizers on students’ comprehension and recall of expository text: A review of the research and implications for practice. Reading and Writing Quarterly, 11, 73-89. Griffin, M., & Robinson, D. (2000). Role of mimeticism and spatiality in textual recall. Contemporary Educational Psychology, 25(2), 125-149. Gurlitt, J., & Renkl, A. (2010). Different concept mapping tasks lead to substantial differences in cognitive processes, learning outcomes, and perceived self- efficacy. Instructional Science, 38(4), 417-433. Haugwitz, M., Nesbit, J., & Sandmann, A. (2010). Cognitive ability and the in- structional efficacy of collaborative concept mapping. Learning and Indi- vidual Differences, 20, 536-543. Jaswal, V., & Markman, E. (2001). Learning proper and common names in infer- ential vs. ostensive contexts. Child Development, 72, 768-776. Jiang, X., & Grabe, W. (2007). Graphic organizers in reading instruction: Research findings and issues. Reading in a Foreign Language, 19(1), 34-55. Katayama, A., & Robinson, D. (2000). Getting students partially involved in note-taking using graphic organizers. Journal of Experimental Education, 68, 119-133. Kendeou, P., van den Broek, P., Helder, A., & Karlsson, J. (2014). A cognitive view of reading comprehension: Implications for reading difficulties. Learning Disabilities, 29(1), 10-16. Kinchin, I. (2014). Concept mapping as a learning tool in higher education: A critical analysis of recent reviews. The Journal of Continuing Higher Edu- cation, 62(1), 39-49. Krug, D., George, B., Hannon, S., & Glover, J. (1989). The effect of outlines and headings on readers’ recall of text. Contemporary Educational Psychology, 14(2), 111-123. Kiewra, K. (1985). Providing the instructor’s notes: An effective addition to stu- dent note taking. Educational Psychologist, 20(1), 33-39. Kools, M., van de Wiel, M. W., Ruiter, R. A., Crüts, A., & Kok, G. (2006). The effect of graphic organizers on subjective and objective comprehension of a health education text. Health Education & Behavior, 33(6), 760-772. Kulhavy, R., White, M., Topp, B., Chan, A., & Adams, J. (1985). Feedback com- plexity and corrective efficiency. Contemporary Educational Psychology, 10(3), 285-291. Lambiotte, J., & Dansereau, D. (1992). Effects of knowledge maps and prior knowledge on recall of science lecture content. Journal of Experimental Education, 60(3), 189-201. Larkin, J., & Simon, H. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11, 65-99. Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 382 Leyu, Q. (2001). A consideration of learners’ individual differences in classroom lan- guage teaching. Memoires of Fukui University of Technology, 31(2), 79-86. Looi, L., & Mustapha, G. (2010). Enhancing writing ability through multiple-intelli- gence strategies. Pertanika Journal of Social Sciences & Humanities, 18, 53-63. Manoli, P., & Papadopoulou, M. (2012). Graphic organizers as a reading strategy: Research findings and issues. Creative Education, 3(3), 348-356. Marefat, H., & Ghahari, S. (2009). (Incorporating) adjunct displays: A step toward facilitation of reading comprehension. Porta Linguarum, 11, 179-188. Mayer, R. (1984). Aids to text comprehension. Educational Psychologist, 19, 30-42. McCagg, E., & Dansereau, D. (1991). A convergent paradigm for examining knowledge mapping as a learning strategy. Journal of Educational Research, 84(6), 317-324. McCrudden, M., Schraw, G., & Lehman, S. (2009). The use of adjunct displays to facilitate comprehension of causal relationships in expository text. In- structional Science, 37, 65-86. McKenzie, W. (2005). Multiple intelligences and instructional technology. Eu- gene: International Society for Technology in Education. McMahon, S., Rose, D., & Parks, M. (2004). Multiple intelligences and reading achievement: An examination of the Teele inventory of multiple intelli- gences. The Journal of Experimental Education, 73(1), 41-52. Nesbit, J., & Adesope, O. (2006). Learning with concept and knowledge maps: A meta-analysis. Review of Educational Research, 76, 413-448. Nicholson-Nelson, K. (1998). Multiple intelligences. New York: Scholastic Profes- sional Books. O’Donnell, A. (1993). Searching for information in knowledge maps and texts. Contemporary Educational Psychology, 18, 222-239. Ozdemir, P., Guneysu, S., & Tekkaya, C. (2006). Enhancing learning through mul- tiple intelligences. Journal of Biological Education, 40(2), 74-78. Paivio, A. (1983). The empirical case for dual coding. In J. Yuille (Ed.), Imagery, memory, and cognition: Essays in honor of Allan Paivio (pp. 307-332). Hillsdale, NY: Erlbaum. Rahmani, M., & Sadeghi, K. (2011). Effects of note-taking training on reading comprehension and recall. Reading Matrix, 11(2), 116-128. Redford, J., Thiede, K., Wiley, J., & Griffin, T. (2012). Concept mapping improves metacomprehension accuracy among 7th graders. Learning and Instruc- tion, 22, 262-270. Rickards, J., & Friedman, F. (1978). The encoding versus the external storage hypoth- esis in note taking. Contemporary Educational Psychology, 3(2), 136-143. Robinson, D. H. (1998). Graphic organizers as aids to text learning. Reading Re- search and Instruction, 37, 85-105. Learner- vs. expert-constructed outlines: Testing the associations with L2 text comprehension and. . . 383 Robinson, D., & Kiewra, K. (1995). Visual argument: Graphic organizers are su- perior to outlines in improving learning from text. Journal of Educational Psychology, 87(3), 455-467. Robinson, D., Katayama, A., & Fan, A. (1996). Evidence for conjoint retention of information encoded from spatial adjunct displays. Contemporary Educa- tional Psychology, 21(3), 221-239. Robinson, D., & Skinner, C. (1996). Why graphic organizers facilitate search pro- cesses: Fewer words or computationally efficient indexing? Contemporary Educational Psychology, 21(2), 166-180. Rowland-Bryant, E., Skinner, C., Skinner, A., Saudargas, R., Robinson, D., & Kirk, E. (2009). Investigating the interaction of graphic organizers and seductive details: Can a graphic organizer mitigate the seductive-details effect? Re- search in the Schools, 16(2), 29-40. Saricaoglu, A., & Arikan, A. (2009). A study of multiple intelligences, foreign lan- guage success, and some selected variables. Journal of Theory and Prac- tice in Education, 5(2), 110-122. Schmidt, R. (1990). The role of consciousness in second language learning. Ap- plied Linguistics, 11(2), 129-158. Schnotz, W. (2014). Integrated model of text and picture comprehension. In R. Mayer (Ed.), The handbook of multimedia learning (pp. 72-103). Cam- bridge: Cambridge University Press. Schroeder, N., Nesbit, J., Anguiano, C., & Adesope, O. (2018). Studying and construct- ing concept maps: A meta-analysis. Educational Psychology Review, 30, 1-25. Shaw, S., Nihalani, P., Mayrath, M., & Robinson, D. (2012). Graphic organizers or graphic overviews? Presentation order effects with computer-based text. Educational Technology Research & Development, 60, 807-820. Stull, A., & Mayer, R. (2007). Learning by doing versus learning by viewing: Three experimental comparisons of learner-generated versus author-provided graphic organizers. Journal of Educational Psychology, 99(4), 808-820. Suzuki, A., Sato, T., & Awazu, S. (2008). Graphic display of linguistic information in English as a foreign language reading. TESOL Quarterly, 42, 591-616. Sweller, J., Van Merrienboer, J., & Paas, F. (1998). Cognitive architecture and in- structional design. Educational Psychology Review, 10(3), 251-296. Tzeng, J. (2010). Designs of concept maps and their impacts on readers’ perfor- mance in memory and reasoning while reading. Journal of Research in Reading, 33, 128-147. Waller, R. (1981). Understanding network diagrams. Paper presented at the an- nual meeting of the American Educational Research Association, Los An- geles. https://eric.ed.gov/?id=ED226695 Sholeh Moradi, Shima Ghahari, Mohammad Abbas Nejad 384 van Gog, T., Kester, L., Nievelstein, F., Giesbers, B., & Paas, F. (2009). Uncovering cognitive processes: Different techniques that can contribute to cognitive load research and instruction. Computers in Human Behavior, 25, 325-331. Van Patten, B. (1996). Input processing and grammar instruction in second lan- guage acquisition. Norwood: Ablex Publishing. Vincent, A., & Ross, D. (2001). Personalize training: Determine learning styles, personality types and multiple intelligences online. The Learning Organi- zation, 8(1), 36-43.