大學是從課室學習邁向獨立自主終身學習的重要過渡階段，倘能在此時期找到有效解讀科學文章訊息的方法，將有助於提升現代公民必備的科學素養。文本連貫性（text cohesion）是影響閱讀理解的重要因素，本研究以文本連貫性對臺灣大學生閱讀科學說明文的理解為研究核心，而臺灣目前並沒有評量大學生說明文閱讀理解能力的測驗，因此本研究之主要目的有二：第一，因著研究需求，發展一套適用於測量大學生說明文閱讀理解能力的測驗；第二，探索文本特徵（即文本連貫性）、讀者特徵（即閱讀理解能力、先備知識）與任務經驗（即閱讀文章加上做測驗為一次任務週期）在科學文章閱讀理解的關係，透過眼動等線上（on-line）歷程資料、測驗等離線（offline）測量資料，以及結合線上與離線的提示回溯放聲思考原案，探討大學生閱讀高低連貫性科學文章時的閱讀理解表現和歷程。研究參與者為120名20—30歲之大學生（含研究生），隨機分派至四種實驗組別，每位參與者皆會閱讀兩篇各約1,500字的地球科學文章，閱讀順序採平衡設計，操弄條件為文本連貫性（高連貫性 vs. 低連貫性）和任務經驗（初次任務 vs. 再次任務）。參與者先進行特徵變項的測量，包括研究者自編《大專生說明文閱讀理解測驗》和《先備知識測驗》，隨後依照分派組別閱讀科學文章，同時錄製其眼動情況，閱讀後實施閱讀表現測驗，包括提示回憶測驗與理解表現測驗。第二次任務的閱讀和測驗結束後再進行提示回溯放聲思考（cued retrospective think-aloud），即播放參與者閱讀時的電腦螢幕畫面與眼動軌跡，請參與者解釋自己是如何進行閱讀的，做為閱讀歷程解釋的輔助。在資料分析的部分，閱讀表現和全文層次、主題層次眼動指標資料採線性混合模型（linear mixed-effects models, LMMs）進行分析。閱讀表現結果發現，在控制文本內容後，文本連貫性對大學生科學文章理解表現的效果會受到任務經驗調節，連貫效果（即高連貫文本比低連貫文本更有利）僅出現於再次任務者的理解表現，而初次任務者則否；另一方面，再次任務者閱讀高連貫文本時比初次任務者有更好的理解表現；從全文層次的眼動資料的確可以發現，再次任務者在高連貫文本的總凝視時間、總凝視次數皆顯著高於初次任務者，顯示有過任務經驗的讀者會調整自己的閱讀方式，投注更多心力在高連貫的新材料上，支持自我調整學習理論（self-regulated learning theory），但任務經驗對於低連貫文本的理解表現和全文層次眼動指標並無影響；至於提示回憶表現則未出現文本連貫性與任務經驗的交互作用。此外，不論在理解表現或提示回憶表現，連貫效果並未受到閱讀能力或先備知識調節，因此能力強化效果假說（ability-as-enhancer hypothesis）或補償假說（compensation hypothesis）並未獲得支持證據；但閱讀能力與先備知識皆產生主要效果，亦即高閱讀能力者與高先備知識者皆有較佳的理解表現和提示回憶表現。眼動資料顯示，閱讀能力越高者解碼科學文章訊息越容易（反映在較低的平均凝視時間），且閱讀能力有可能與主題段落較快的理解整合有關（反映在其中一篇文章的主題層次再次注視時間越少）；而先備知識越高，主題層次每字凝視時間與首次每字注視時間越少，表示處理科學文章訊息需花費的認知資源越少，尤其是初始處理。概念層次眼動指標資料採滯後序列分析（lag sequential analyses, LSA），結果顯示再次任務者閱讀高連貫文本會進行較為密集的概念參照，尤其是在因果集合、比較對照等結構性強的子主題內會有較多的概念間視覺轉移；初次任務者在閱讀低連貫文本時經常做的是跨主題的參照，再次任務者在閱讀低連貫文本反而增加的是局部參照，或許這也部分反映了任務經驗增加沒有帶來低連貫文本閱讀表現進步的原因。閱讀階段層次眼動指標資料使用三次成長模型（cubic growth curve analysis, GCA）進行分析，將凝視時間切割為總閱讀時間的每10%為一個波段，針對材料中各個別頁面形成縱貫資料，結果顯示科學文章第一頁在閱讀初期有較多凝視時間，但趨勢持續下降，隨後凝視又會在第八波段左右再度增加，顯示閱讀中後期讀者會回到首頁重讀，至於其他頁面的凝視時間通常呈現先升後降的趨勢，但依照頁面順序，由升轉降的反曲點位置會有波段遞移的情況，到了閱讀中後期又會緩升，但並非每一頁都出現這種斜率轉正的曲線，顯示到了閱讀中後期通常為選擇性的認知處理，帶有特定的閱讀目的。整體而言，本研究為Kintsch建構—整合模式中的表徵層次提供了實徵證據，以歷程資料和測量資料共同描繪大學生科學文章閱讀理解的樣貌，呈現文本特徵與讀者特徵交互影響的情況，強調理解模型需要考慮文本特徵（即文本連貫性）的潛在複雜性，同時涵蓋一些支持閱讀理解的其他歷程（例如：自我調整），以及通常需要納入的個別差異因子（即閱讀理解能力和先備知識）。最後提出理論與實務上的啟示、限制，以及未來可能的研究方向。

College marks an important transition from in-class learning to lifelong learning. Therefore, if students can develop an effective approach to acquire information from science text during this period, their scientific literacy, considered as a necessary ability for modern citizens, can be improved as a result. However, even though expository texts are common in scientific reading, no test is currently available for evaluating the expository reading comprehension skills of college students in Taiwan. Hence, the first aim of this study was to develop an acceptable reading comprehension ability test for college students. Besides, since text cohesion is regarded as an important factor of reading comprehension, the second aim focused on the role of cohesion effect in expository scientific reading for Taiwanese college students. That is, the relationship between text features (i.e., text cohesion), reader features (i.e., reading comprehension skills, prior knowledge) and task experience (i.e., text reading and test practicing as a task cycle) in science text reading comprehension was explored through online measures (i.e., eye movements), offline measurement (i.e., tests), and combined online and offline measures (i.e., cued retrospectively think-aloud, CRTA). One hundred and twenty college and graduate students aged 20-30 participated in the experiment, randomly assigned to four experimental groups. Each participant read two earth science articles containing about 1,500 words each, with a balanced reading order. Text cohesion (high cohesion vs. low cohesion) and task experience (cycle 1 vs. cycle 2) were manipulated. A task cycle involves the following phases. The demographic and characteristic variables of participants were first measured, including the self-derived “Reading Comprehension Test of Expository Text for College Students” and “Prior Knowledge Test,” and then they would read the assigned science text, with their eye movements recorded in the meantime. After reading, performance tests (including cued recalls and comprehension performance tests) were administrated. Once the two task cycles were done, the cued retrospective think-aloud would be performed, in which participants verbalized their thoughts while watching their eye-movement recordings.
As for data analysis, three analysis methods were carried out. Firstly, the reading performance, full-text-level and topic-level eye-tracking indicators were analyzed with linear mixed-effect models (LMMs). The results of reading performance showed that after controlling for text content, the effect of text cohesion on the comprehension performance was moderated by task experience, and the cohesion effect (that is, high-cohesion texts were more favorable than low-cohesion texts) only appeared in Cycle 2. In the high-cohesion condition, the participants had better comprehension performance in Cycle 2 than those in Cycle 1. Besides, the results of the full-text-level eye-tracking indicators showed that the readers reading high-cohesion texts had significantly higher total fixation duration and total fixation count in Cycle 2 than those in Cycle 1, indicating that readers who had task experience would regulate their reading strategies and invest more effort in their next reading, which supports the self-regulated learning (SRL) theory. However, task experience had no effect on comprehension performance and full-text-level eye-tracking indicators in the low-cohesion condition. As for cued recall, there was no interaction between text cohesion and task experience. In addition, cohesion effects were not moderated by reading comprehension skills or prior knowledge, neither on comprehension performance nor on cued recall. Therefore, no supporting evidence was found for the ability-as-enhancer hypothesis or the compensation hypothesis. However, both reading skills and prior knowledge had main effects, that is, those with high reading skills and high prior knowledge had better comprehension and cued recall performance. Eye-tracking data showed that readers with high reading skills were better at decoding science text (reflected on shorter mean fixation duration), and that reading skills were likely to be associated with more efficient integration of information in each subtopic, indicated by the shorter topic-level second-pass fixation duration per character found in one of the reading articles. Also, the higher the prior knowledge, the shorter the total fixation duration per character and the first-pass fixation duration per character at the topic level, indicating that prior knowledge helped the cognitive processing of science text, especially in initial processing. In the second analysis method, the concept-level eye-tracking indicators were analyzed by lag sequential analyses (LSA). The results showed that readers who read high-cohesion texts in Cycle 2 would make more visual transitions between concepts, especially in highly structural subtopics made up of more causation and comparison. By contrast, readers who read low-cohesion texts in Cycle 1 often made cross-topic references, while the usage of local references in Cycle 2 increased instead, which might explain why increased task experience did not lead to improved reading performance in the low-cohesion condition. As for the last analysis method, the phase-level eye-tracking indicators was analyzed using cubic growth curve analysis (GCA), and the fixation duration was divided into ten waves (every 10% of the total reading time), forming longitudinal data for each individual page of the science text. The results showed that the fixation duration of the first page of science text was high in the early phase of reading but declined afterwards, and then increased again around in the eighth wave, indicating that readers were inclined to reread the first page in mid- and late-stage of reading. As for the fixation duration of other pages, the duration tended to increase then decline in each of the following pages, and the position of the first inflection point from rising to falling had a wave transition along with the page order. However, a second inflection point from falling to mildly rising was only found in some pages, indicating that readers would perform selective cognitive processing in the mid- and late-stages of reading in response to the specific reading purpose.
Overall, this study provided empirical evidence for the representational level and the role of prior knowledge in Kintsch’s construction–integration model (CI model), and used process data and measurement data to jointly describe college students’ reading comprehension of science text. In addition, this study further highlighted the interaction between text characteristics and reader characteristics, emphasizing that comprehension models need to take the underlying complexity of text features (i.e., text cohesion) into account. Furthermore, several aspects were also considered in this research, including the processes that support reading comprehension (e.g., self-regulation), and individual differences, which also often need to be incorporated (i.e., reading comprehension skills and prior knowledge). Finally, the theoretical and practical implications, limitations, and possible future directions were addressed in the last section.

王木榮、董宜俐（2006）：《國民小學閱讀理解測驗》。心理出版社。[Wang, M.-R., & Dong, Y.-L. (2006). Reading Comprehension Test for Elementary School Students. Psychological Publishing.]
王孜甯、簡郁芩（2022）：〈科學圖文閱讀眼動研究之系統回顧〉。《教育心理學報》，53，773–800。[Wang, T.-N., & Jian, Y.-C. (2022). A systematic review of eye-tracking studies on text-diagram science reading. Bulletin of Educational Psychology, 53, 773–799.] https://doi.org/10.6251/BEP.202206_53(4).0001
李奕璇、周業太、宋曜廷（2021）：〈中文閱讀能力適性診斷評量編製研究〉。《教育心理學報》，53，285–305。[Lee, Y.-H., Chou, Y.-T., & Sung, Y.-T. (2021). Development and validation of a diagnostic assessment of Chinese competence system. Bulletin of Educational Psychology, 53, 285–305.] https://doi.org/10.6251/bep.202112_53(2).0002
宋曜廷、陳茹玲、李宜憲、查日龢、曾厚強、林維駿、張道行、張國恩（2013）：〈中文文本可讀性探討：指標選取、模型建立與效度驗證〉。《中華心理學刊》，55，75–106。[Sung, Y.-T., Chen, R.-L., Lee, Y.-S., Cha, J.-H., Tseng, H.-C., W.-C., Chang, T.-H., & Chang, K.-E. (2013). Investigating Chinese text readability: Linguistic features, modeling, and validation. Chinese Journal of Psychology, 55, 75–106.] https://doi.org/10.6129/CJP.20120621
林怡君、張麗麗、陸怡琮（2013）：〈Rasch模式建置國小高年級閱讀理解測驗〉。《教育心理學報》，45，39–61。[Lin, I-C., Chang, L., Lu, I-C. (2013). The development of Reading Comprehension Test for 5th and 6th graders using the Rasch model. Bulletin of Educational Psychology, 45, 39–61.] https://doi.org/10.6251/bep.20121128
林珊如、謝明宜（2017）：〈起始篇：眼動技術在數位學習發展的初步成果與挑戰〉。見孫春在、林珊如、袁賢銘、王淑玲、王岱伊、高宜敏、謝吉隆、雷佩嵐、林志鴻（主編），《數位學習者之眼：應用眼動技術於數位學習研究》，頁13–45。國立交通大學出版社。[Lin, S. S. J., & Hsieh, M. Y. (2017). Beginning: The initial progress and challenges of eye-tracking technology in the studies of digital learning. In C.-T. Sun, S. S. J. Lin, S.-M. Yuan, S.-L. Wang, D.-Y. Wang, Y.-M. Kao, J.-L. Hsieh, P.-L. Lei, & C.-H. Lin (Eds.), Digital learnes’ eyes (pp. 13–45). Natioal Chiao Tung University Press.]
林寶貴、錡寶香（2000）：〈中文閱讀理解測驗之編製〉。《特殊教育研究學刊》，19，79–104。[Lin, B.-G., & Chi, P.-H. (2000). The development of Reading Comprehension Test. Bulletin of Special Education, 19, 79–104.]
柯華葳（1999）：〈閱讀理解困難篩選測驗〉。《測驗年刊》，46（2），1–11。[Ko, H.-W. (1999). Reading Comprehension Screening Test. Psychological Testing, 46(2), 1–11.]
柯華葳、陳明蕾、廖家寧（2005）：〈詞頻、詞彙類型與眼球運動型態：來自篇章閱讀的證據〉。《中華心理學刊》，47，381–398。[Ko, H.-W., Chen, M.-L., & Liao, C.-N. (2005). Frequency effect, word class and eye movements: Evidence from text reading. Chinese Journal of Psychology, 47, 381–398.] http://doi.org/10.6129/cjp.2005.4704.06
柯華葳、陳冠銘（2011）：〈文章結構標示與閱讀理解–以低年級學生為例〉。《教育心理學報》，36，185–200。[Ko, H.-W., & Chen, K.-M. (2011). Improving children’s reading comprehension with highlighted text structures. Bulletin of Educational Psychology, 36, 185–200.] http://doi.org/10.6251/BEP.20041008
柯華葳、詹益綾（2006a）：《國民小學二至六年級閱讀理解篩選測驗》。教育部特殊教育小組。[Ko, H.-W., & Chan, Y.-L. (2006a). Reading comprehension screening test for second to sixth graders. Department of Student Affairs and Special Education, Ministry of Education, Taiwan.]
柯華葳、詹益綾（2006b）：《國民中學閱讀推理測驗》。教育部特殊教育小組。[Ko, H.-W., & Chan, Y.-L. (2006b). Inferential Comprehension Test for junior high school students. Department of Student Affairs and Special Education, Ministry of Education, Taiwan.]
柯華葳、詹益綾（2007）：〈國民中學閱讀推理篩選測驗編製報告〉。《測驗學刊》，54，429–449。[Ko, H.-W., & Chan, Y.-L. (2007). Reading Comprehension Screening Test for Junior High School Students. Psychological Testing, 54, 429-449.] https://doi.org/10.7108/pt.200712.0429
張祐瑄、蘇宜芬（2007）：《大專生閱讀理解能力測驗之編製與信效度研究》。未出版手稿。[Chang, Y.-H., & Su, Y.-F. (2007). The development and research of Reading Comprehension Ability Test for College Students. Unpublished manuscript.]
連啓舜、曾玉村（2018）：〈兒童摘要的推論歷程〉。《教育心理學報》，49，537–556。[Lien, C.-S., & Tzeng, Y. (2011). The inference processes of summarization. Bulletin of Educational Psychology, 49, 537–556.] http://doi.org/10.6251/bep.201806_49(4).0002
陳學志、賴惠德、邱發忠（2010）：〈眼球追蹤技術在學習與教育上的應用〉。《教育科學研究期刊》，55（4），39–68。[Chen, H.-C., Lai, H.-D., & Chiu, F.-C. (2010). Eye tracking technology for learning and education. Journal of Research in Education Sciences, 55(4), 39–68.] http://doi.org/10.3966/2073753X2010125504002
曾秋華、游錦雲、陳欣希（2018）：〈以PIRLS架構和Rasch模式建構閱讀理解測驗〉。市北教育學刊，60，1–30。[Tseng, C.-H., Yu, C.-Y., & Chen, H.-H. (2018). Developing reading comprehension test using PIRLS reading framework and the Rasch Model. Journal of Education of Taipei Municipal University of Education, 60, 1–30.] https://doi.org/10.7036/jeut.201808_60.0001
黃秀霜、曾雅瑛、甘孟龍、許力云、黃品甄（2019）：〈「國中生線上閱讀理解能力測驗」之發展及相關因素之研究〉。《測驗學刊》，66，377–401。[Huang, H.-S., Tseng, Y.-Y., Gan, M.-L., Hsu, L.-Y., & Huang, P.-C. (2019). Research on the development and related factors of the online reading comprehension assessment for junior high school students. Psychological Testing, 66, 377–401.]
劉佩雲（2020）：〈國小中高年級學童文章結構辨識與閱讀理解之研究〉。《課程與教學》，23，143–164。[Liu, P.-Y. (2020). Effects of text structures identification on 3th graders’ to 6th graders’ reading comprehension. Curriculum & Instruction Quarterly, 23, 143–164.] https://doi.org/10.6384/ciq.202001_23(1).0006
劉宜芳、柯華葳（2014）：〈國小學生「線上閱讀素養測驗」之編製與線上閱讀能力表現之初探〉。《測驗學刊》，61，509–532。[Liu, I.-F., & Ko, H.-W. (2014). Developing online reading skill test to assess elementary students’ online reading performance, Psychological Testing, 61, 509–532.]
蔡介立、顏妙璇、汪勁安（2005）：〈眼球移動測量及在中文閱讀研究之應用〉。《應用心理研究》，28，91–104。[Tsai, J.-L., Yen, M.-H., & Wang, C.-A. (2005). Recoding on eye movements and its application on Chinese reading. Research in Applied Psychology, 28, 91–104.]
鄭可萱、李松濤（2018）：〈當科學素養與閱讀素養相遇：高中學生科學新聞閱讀策略之實驗研究〉。《教育科學研究期刊》，63（4），157–192。[Zheng, K.-H. & Lee, S.-T. (2018). When science literacy and reading literacy meet: Experimental study of science news reading strategy for high school students. Journal of Research in Education Sciences, 63(4), 157–192.] https://doi.org/10.6209/jories.201812_63(4).0006
盧貞諺（2020）：《作筆記策略教學對高中生閱讀理解之影響研究》（未出版碩士論文），國立臺灣師範大學。[Lu, C.-Y. (2020). The effects of “note-taking strategy instruction”on reading comprehension in senior high school students (Unpublished master’s thesis), National Taiwan Normal University.]
簡郁芩、吳昭容（2012）：〈以眼動型態和閱讀測驗表現探討箭頭在科學圖文閱讀中的圖示效果〉。《中華心理學刊》，54，385–402。[Jian, Y.-C., & Wu, C.-J. (2012). The effect of arrows in an illustration when reading scientific text: Evidence from eye movements and reading tests. Chinese Journal of Psychology, 54, 385–402.] https://doi.org/10.6129/cjp.2012.5403.07
蘇宜芬、洪儷瑜、陳心怡、陳柏熹（2015）：《閱讀理解成長測驗（四至六年級版）》。中國行為科學社。[Su, Y.-F., Hung, L.-Y., Chen, H.-Y., & Chen, P.-H. (2015). Progress Monitoring Test of Reading Comprehension for grade 4–6 students. Chinese Behavioral Science Corporation.]
蘇宜芬、洪儷瑜、陳柏熹、陳心怡（2018）：〈閱讀理解成長測驗之編製研究〉。《教育心理學報》。49，557–580。[Su, Y.-F., Hung, L.-Y., Chen, P.-H., & Chen, H.-Y.(2018). The development of progress monitoring test of reading comprehension. Bulletin of Educational Psychology, 49, 557–580.] https://doi.org/10.6251/bep.201806_49(4).0003
Agarwal, P. K., Nunes, L. D., & Blunt, J. R. (2021). Retrieval practice consistently benefits student learning: A systematic review of applied research in schools and classrooms. Educational Psychology Review, 33, 1409–1453. https://doi.org/10.1007/s10648-021-09595-9
Alemdag, E., & Cagiltay, K. (2018). A systematic review of eye tracking research on multimedia learning. Computers & Education, 125, 413–428. https://doi.org/10.1016/j.compedu.2018.06.023
Andrews, S., Miller, B., & Rayner, K. (2004). Eye movements and morphological segmentation of compound words: There is a mouse in mousetrap. European Journal of Cognitive Psychology, 16, 285–311. https://doi.org/10.1080/09541440340000123
Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55, 469–480. https://doi.org/10.1037/0003-066X.55.5.469
Arnold, K. M., & McDermott, K. B. (2013a). Free recall enhances subsequent learning. Psychonomic Bulletin & Review, 20, 507–513. https://doi.org/10.3758/s13423-012-0370-3
Arnold, K. M., & McDermott, K. B. (2013b). Test-potentiated learning: Distinguishing between direct and indirect effects of tests. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 940–945. https://doi.org/10.1037/a0029199
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory & Language, 59, 390–412. https://doi.org/10.1016/j.jml.2007.12.005
Bakeman, R., & Gottman, J. M. (1997). Observing interaction: An introduction to sequential analysis (2nd ed.). Cambridge University Press.
Bender, L., Renkl, A., & Eitel, A. (2021). When and how seductive details harm learning. A study using cued retrospective reporting. Applied Cognitive Psychology, 35, 948–959. https://doi.org/10.1002/acp.3822
Best, R. M., Floyd, R. G., & McNamara, D. S. (2008). Differential competencies contributing to children’s comprehension of narrative and expository texts. Reading Psychology, 29, 137–164. https://doi.org/10.1080/02702710801963951
Borrero, F., Hess, F. S., Hsu, C. H. J., Kunze, G., Leslie, S. A., Letro, S., Manga, M., Sharp, L., Snow, T., Zike, D., & Geographic, N. (2009). Earth science: Geology, the environment, and the universe. The McGraw-Hill Companies.
Brauer, M., & Curtin, J. J. (2018). Linear mixed-effects models and the analysis of nonindependent data: A unified framework to analyze categorical and continuous independent variables that vary within-subjects and/or within-items. Psychological Methods, 23, 389–411. https://doi.org/10.1037/met0000159
Britton, B. K., & Gülgöz, S. (1991). Using Kintsch’s computational model to improve instructional text: Effects of repairing inference calls on recall and cognitive structures. Journal of Educational Psychology, 83, 329–345. https://doi.org/10.1037/0022-0663.83.3.329
Carvalho, P. F., McLaughlin, E. A., & Koedinger, K. R. (2022). Varied practice testing is associated with better learning outcomes in self-regulated online learning. Journal of Educational Psychology. Advance online publication. https://doi.org/10.1037/edu0000754
Catrysse, L., Gijbels, D., & Donche, V. (2018). It is not only about the depth of processing: What if eye am not interested in the text? Learning and Instruction, 58, 284–294. https://doi.org/10.1016/j.learninstruc.2018.07.009
Chall, J. S. (1996). Stages of reading development (2nd ed.). Harcourt Brace College Publishers.
Chen, C.-M., Chang, C., & Chen, Y.-T. (2021). A character social network relationship map tool to facilitate digital humanities research. Library Hi Tech, ahead-of-print (ahead-of-print). https://doi.org/10.1108/LHT-08-2020-0194
Choi, H., & Lee, H. S. (2020). Knowing is not half the battle: The role of actual test experience in the forward testing effect. Educational Psychology Review, 32, 765–789. https://doi.org/10.1007/s10648-020-09518-0
Clinton, V., Taylor, T., Bajpayee, S., Davison, M. L., Carlson, S. E., & Seipel, B. (2020). Inferential comprehension differences between narrative and expository texts: A systematic review and meta-analysis. Reading and Writing, 33, 2223–2248. https://doi.org/10.1007/s11145-020-10044-2
Coskun, A., & Cagiltay, K. (2022). A systematic review of eye-tracking-based research on animated multimedia learning. Journal of Computer Assisted Learning, 38, 581–598. https://doi.org/10.1111/jcal.12629
Dancey, C., & Reidy, J. (2017). Statistics without Maths for Psychology (7th ed.). Pearson.
de Jonge, M., Tabbers, H. K., & Rikers, R. M. J. P. (2015). The effect of testing on the retention of coherent and incoherent text material. Educational Psychology Review, 27, 305–315. https://doi.org/10.1007/s10648-015-9300-z
Diakidoy, I.-A. N., Mouskounti, T., Fella, A., & Ioannides, C. (2016). Comprehension processes and outcomes with refutation and expository texts and their contribution to learning. Learning and Instruction, 41, 60–69. https://doi.org/10.1016/j.learninstruc.2015.10.002
Diakidoy, I.-A. N., Mouskounti, T., & Ioannides, C. (2011). Comprehension and learning from refutation and expository texts. Reading Research Quarterly, 46, 22–38. https://doi.org/10.1598/RRQ.46.1.2
Donker, A. S., de Boer, H., Kostons, D., Dignath van Ewijk, C. C., & van der Werf, M. P. C. (2014). Effectiveness of learning strategy instruction on academic performance: A meta-analysis. Educational Research Review, 11, 1–26. https://doi.org/10.1016/j.edurev.2013.11.002
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4–58. https://doi.org/10.1177/1529100612453266
Eitel, A. (2016). How repeated studying and testing affects multimedia learning: Evidence for adaptation to task demands. Learning and Instruction, 41, 70–84. https://doi.org/10.1016/j.learninstruc.2015.10.003
Eitel, A., Martin Benito, S., & Scheiter, K. (2017). Do it twice! Test-taking fosters repeated but not initial study of multimedia instruction. Learning and Instruction, 52, 36–45. https://doi.org/10.1016/j.learninstruc.2017.04.003
Endres, T., & Renkl, A. (2015). Mechanisms behind the testing effect: an empirical investigation of retrieval practice in meaningful learning. Frontiers in Psychology, 6, 1054. https://doi.org/10.3389/fpsyg.2015.01054
Fernandez, J., & Jamet, E. (2017). Extending the testing effect to self-regulated learning. Metacognition and Learning, 12, 131–156. https://doi.org/10.1007/s11409-016-9163-9
Follmer, D. J., & Sperling, R. A. (2018). Interactions between reader and text: Contributions of cognitive processes, strategy use, and text cohesion to comprehension of expository science text. Learning and Individual Differences, 67, 177–187. https://doi.org/10.1016/j.lindif.2018.08.005
Gagné, E. D. (1985). The cognitive psychology of school learning. Little, Brown and Company.
Godfroid, A., Ahn, J., Choi, I. N. A., Ballard, L., Cui, Y., Johnston, S., Lee, S., Sarkar, A., & Yoon, H.-J. (2018). Incidental vocabulary learning in a natural reading context: An eye-tracking study. Bilingualism: Language and Cognition, 21, 563–584. https://doi.org/10.1017/S1366728917000219
Graesser, A. C., León, J. A., & Otero, J. (2002). Introduction to the psychology of science text comprehension. In J. Otero, J. A. León, & A. C. Graesser (Eds.), Psychology of science text comprehension (pp. 1–15). Lawrence Erlbaum Associates Publishes.
Graesser, A. C., McNamara, D. S., Louwerse, M. M., & Cai, Z. (2004). Coh-Metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, & Computers, 36, 193–202. https://doi.org/10.3758/BF03195564
Greene, J. A., & Azevedo, R. (2009). A macro-level analysis of SRL processes and their relations to the acquisition of a sophisticated mental model of a complex system. Contemporary Educational Psychology, 34, 18–29. https://doi.org/10.1016/j.cedpsych.2008.05.006
Häikiö, T., Heikkilä, T. T., & Kaakinen, J. K. (2018). The effect of syllable-level hyphenation on reading comprehension: Evidence from eye movements. Journal of Educational Psychology, 110, 1149–1159. https://doi.org/10.1037/edu0000261
Hall, S. S., Kowalski, R., Paterson, K. B., Basran, J., Filik, R., & Maltby, J. (2015). Local text cohesion, reading ability and individual science aspirations: Key factors influencing comprehension in science classes. British Educational Research Journal, 41, 122–142. https://doi.org/10.1002/berj.3134
Hall, S. S., Maltby, J., Filik, R., & Paterson, K. B. (2016). Key skills for science learning: the importance of text cohesion and reading ability. Educational Psychology, 36, 191–215. https://doi.org/10.1080/01443410.2014.926313
Hebert, M., Bohaty, J. J., Nelson, J. R., & Brown, J. (2016). The effects of text structure instruction on expository reading comprehension: A meta-analysis. Journal of Educational Psychology, 108, 609–629. https://doi.org/10.1037/edu0000082
Heck, R. H., Thomas, S. L., & Tabata, L. N. (2013). Multilevel and longitudinal modeling with IBM SPSS (2nd ed.). Routledge.
Höffler, T. N., Koć-Januchta, M., & Leutner, D. (2017). More evidence for three types of cognitive style: Validating the object-spatial imagery and verbal questionnaire using eye tracking when learning with texts and pictures. Applied Cognitive Psychology, 31, 109–115. https://doi.org/10.1002/acp.3300
Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & Van de Weijer, J. (2011). Eye tracking: A comprehensive guide to methods and measures. OUP Oxford.
Hu, J., & Gao, X. (2017). Using think-aloud protocol in self-regulated reading research. Educational Research Review, 22, 181–193. https://doi.org/10.1016/j.edurev.2017.09.004
Hyönä, J., & Kaakinen, J. K. (2019). Eye movements during reading. In C. Klein & U. Ettinger (Eds.), Eye movement research: An introduction to its scientific foundations and applications (pp. 239–274). Springer International Publishing. https://doi.org/10.1007/978-3-030-20085-5_7
Hyönä, J., Lorch, R. F., Jr., & Rinck, M. (2003). Eye movement measures to study global text processing. In R. Radach, J. Hyönä, & H. Deubel (Eds.), The mind’s eye: Cognitive and applied aspects of eye movement research (pp. 313–334). Elsevier. https://doi.org/10.1016/B978-044451020-4/50018-9
Hyönä, J., Lorch, R. F., Jr., & Kaakinen, J. K. (2002). Individual differences in reading to summarize expository text: Evidence from eye fixation patterns. Journal of Educational Psychology, 94, 44–55. https://doi.org/10.1037/0022-0663.94.1.44
International Association for the Evaluation of Educational Achievement (IEA). (2017). Methods and procedures in PIRLS 2016. TIMSS & PIRLS International Study Center.
Ito, A., Pickering, M. J., & Corley, M. (2018). Investigating the time-course of phonological prediction in native and non-native speakers of English: A visual world eye-tracking study. Journal of Memory and Language, 98, 1–11. https://doi.org/10.1016/j.jml.2017.09.002
Izawa, C. (1971). The test trial potentiating model. Journal of Mathematical Psychology, 8, 200–224. https://doi.org/10.1016/0022-2496(71)90012-5
Jian, Y.-C. (2017). Eye-movement patterns and reader characteristics of students with good and poor performance when reading scientific text with diagrams. Reading and Writing, 30, 1447–1472. https://doi.org/10.1007/s11145-017-9732-6
Jian, Y.-C. (2019). Reading instructions facilitate signaling effect on science text for young readers: An eye-movement study. International Journal of Science and Mathematics Education, 17, 503–522. https://doi.org/10.1007/s10763-018-9878-y
Jian, Y.-C. (2022). Using an eye tracker to examine the effect of prior knowledge on reading processes while reading a printed scientific text with multiple representations. International Journal of Science Education, 44, 1–21. https://doi.org/10.1080/09500693.2022.2072013
Jian, Y.-C., & Ko, H.-W. (2017). Influences of text difficulty and reading ability on learning illustrated science texts for children: An eye movement study. Computers & Education, 113, 263–279. https://doi.org/10.1016/j.compedu.2017.06.002
Jian, Y.-C., Su, J.-H., & Hsiao, Y.-R. (2019). Differentiated processing strategies for science reading among sixth-grade students: Exploration of eye movements using cluster analysis. Computers & Education, 142, Article 103652. https://doi.org/10.1016/j.compedu.2019.103652
Just, M. A., & Carpenter, P. A. (1980). A theory of reading: From eye fixations to comprehension. Psychological Review, 87, 329–354. https://doi.org/10.1037/0033-295X.87.4.329
Kaakinen, J. K. (2021). What can eye movements tell us about visual perception processes in classroom contexts? Commentary on a special issue. Educational Psychology Review, 33, 169–179. https://doi.org/10.1007/s10648-020-09573-7
Kaakinen, J. K., Hyönä, J., & Keenan, J. M. (2003). How prior knowledge, WMC, and relevance of information affect eye fixations in expository text. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 447–457. https://doi.org/10.1037/0278-7393.29.3.447
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38, 23–31. https://doi.org/10.1207/S15326985EP3801_4
Karpicke, J. D., & Aue, W. R. (2015). The testing effect is alive and well with complex materials. Educational Psychology Review, 27, 317–326. https://doi.org/10.1007/s10648-015-9309-3
Karpicke, J. D., Lehman, M., & Aue, W. R. (2014). Retrieval-based learning: An episodic context account. In B. H. Ross (Ed.), Psychology of Learning and Motivation (Vol. 61, pp. 237–284). Academic Press. https://doi.org/10.1016/B978-0-12-800283-4.00007-1
Kendeou, P., & van den Broek, P. (2007). The effects of prior knowledge and text structure on comprehension processes during reading of scientific texts. Memory & Cognition, 35, 1567–1577. https://doi.org/10.3758/BF03193491
Ketzer-Nöltge, A., Schweppe, J., & Rummer, R. (2019). Is the seductive details effect moderated by mood? An eye-tracking study. Applied Cognitive Psychology, 33, 62–70. https://doi.org/10.1002/acp.3487
King, A. J., Bol, N., Cummins, R. G., & John, K. K. (2019). Improving visual behavior research in communication science: An overview, review, and reporting recommendations for using eye-tracking methods. Communication Methods and Measures, 13, 149–177. https://doi.org/10.1080/19312458.2018.1558194
Kintsch, E. (1990). Macroprocesses and microprocesses in the development of summarization skill. Cognition and Instruction, 7, 161–195.
Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction-integration model. Psychological Review, 95, 163–182. https://doi.org/10.1037/0033-295X.95.2.163
Kintsch, W. (1992). A cognitive architecture for comprehension. In J. Pick, H. L., P. W. van den Broek, & D. C. Knill (Eds.), Cognition: Conceptual and methodological issues (pp. 143–163). American Psychological Association.
Kintsch, W. (1998). Comprehension: A paradigm for Cognition. Cambridge University Press.
Kintsch, W. (2005). An overview of top-down and bottom-up effects in comprehension: The CI perspective. Discourse Processes, 39(2–3), 125–128. https://doi.org/10.1080/0163853X.2005.9651676
Kintsch, W. (2018). Revisiting the Construction-Integration Model of text comprehension and its implications for instruction. In D. E. Alvermann, N. J. Unrau, M. Sailors, & R. B. Ruddell (Eds.), Theoretical models and processes of literacy (7th ed., pp. 178–203). Routledge. https://doi.org/10.4324/9781315110592
Kintsch, W., & Rawson, K. A. (2005). Comprehension. In M. J. Snowling, & C. Hulme (Eds.), The science of reading: A handbook (pp. 211–226). Blackwell.
Kintsch, W., & van Dijk, T. A. (1978). Toward a model of text comprehension and production. Psychological Review, 85, 363–394. https://doi.org/10.1037/0033-295X.85.5.363
Kühl, T., Fehringer, B. C. O. F., & Münzer, S. (2022). Unifying the ability-as-compensator and ability-as-enhancer hypotheses. Educational Psychology Review, 34, 1063–1095. https://doi.org/10.1007/s10648-021-09650-5
Lai, M.-L., Tsai, M.-J., Yang, F.-Y., Hsu, C.-Y., Liu, T.-C., Lee, S. W.-Y., Lee, M.-H., Chiou, G.-L., Liang, J.-C., & Tsai, C.-C. (2013). A review of using eye-tracking technology in exploring learning from 2000 to 2012. Educational Research Review, 10, 90–115. https://doi.org/10.1016/j.edurev.2013.10.001
Laugksch, R. C. (2000). Scientific literacy: A conceptual overview. Science Education, 84, 71-94. https://doi.org/10.1002/(SICI)1098-237X(200001)84:1<71::AID-SCE6>3.0.CO;2-C
Lee, H. S., & Ha, H. (2019). Metacognitive judgments of prior material facilitate the learning of new material: The forward effect of metacognitive judgments in inductive learning. Journal of Educational Psychology, 111, 1189–1201. https://doi.org/10.1037/edu0000339
Lehman, S., & Schraw, G. (2002). Effects of coherence and relevance on shallow and deep text processing. Journal of Educational Psychology, 94, 738–750. https://doi.org/10.1037/0022-0663.94.4.738
Lien, C.-S. (2013). Text coherence, reading ability, and children’s scientific understanding. Bulletin of Educational Psychology, 44, 875–904.
Linderholm, T., Everson, M. G., van den Broek, P., Mischinski, M., Crittenden, A., & Samuels, J. (2000). Effects of causal text revisions on more- and less-skilled readers’ comprehension of easy and difficult texts. Cognition and Instruction, 18, 525–556. https://doi.org/10.1207/S1532690XCI1804_4
Liversedge, S. P., & Findlay, J. M. (2000). Saccadic eye movements and cognition. Trends in Cognitive Sciences, 4, 6–14. https://doi.org/10.1016/S1364-6613(99)01418-7
Lorch, R. F., Jr., (2015). What about expository text? In E. J. O'Brien, A. E. Cook, & R. F. Jr. Lorch, (Eds.), Inferences during reading (pp. 348–361). Cambridge University Press.
Lorch, R. F., Jr., & Lorch, E. P. (1995). Effects of organizational signals on text-processing strategies. Journal of Educational Psychology, 87, 537–544. https://doi.org/10.1037/0022-0663.87.4.537
Magezi, D. A. (2015). Linear mixed-effects models for within-participant psychology experiments: an introductory tutorial and free, graphical user interface (LMMgui). Frontiers in Psychology, 6, Article 2. https://doi.org/10.3389/fpsyg.2015.00002
Marshak, S., & Rauber, R. (2017). Earth science: The earth, the atmosphere, and space. W. W. Norton & Company.
Mason, L., Pluchino, P., & Tornatora, M. C. (2013). Effects of picture labeling on science text processing and learning: Evidence from eye movements. Reading Research Quarterly, 48, 199–214. https://doi.org/10.1002/rrq.41
Mason, L., Pluchino, P., & Tornatora, M. C. (2016). Using eye-tracking technology as an indirect instruction tool to improve text and picture processing and learning [Article]. British Journal of Educational Technology, 47, 1083–1095. https://doi.org/10.1111/bjet.12271
Mason, L., Pluchino, P., Tornatora, M. C., & Ariasi, N. (2013). An eye-tracking study of learning from science text with concrete and abstract illustrations. Journal of Experimental Education, 81, 356–384. https://doi.org/10.1080/00220973.2012.727885
Mason, L., Tornatora, M. C., & Pluchino, P. (2013). Do fourth graders integrate text and picture in processing and learning from an illustrated science text? Evidence from eye-movement patterns. Computers & Education, 60, 95–109. https://doi.org/10.1016/j.compedu.2012.07.011
Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning. Journal of Educational Psychology, 86, 389–401. https://doi.org/10.1037/0022-0663.86.3.389
McCrudden, M. T., Magliano, J. P., & Schraw, G. (2011). Relevance in text comprehension. In M. T. McCrudden, J. P. Magliano, & G. Schraw (Eds.), Text relevance and learning from text. (pp. 1–17). IAP Information Age Publishing.
McNamara, D. S. (2001). Reading both high-coherence and low-coherence texts: Effects of text sequence and prior knowledge. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 55, 51–62. https://doi.org/10.1037/h0087352
McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14, 1–43. https://doi.org/10.1207/s1532690xci1401_1
McNamara, D. S., & Kintsch, W. (1996). Learning from texts: Effects of prior knowledge and text coherence. Discourse Processes, 22, 247–288. https://doi.org/10.1080/01638539609544975
McNamara, D. S., & Magliano, J. (2009). Toward a comprehensive model of comprehension. In B. H. Ross (Ed.), The Psychology of Learning and Motivation (Vol. 51, pp. 297–384). Elsevier Academic Press. https://doi.org/10.1016/S0079-7421(09)51009-2
Meyer, B. J. F., Brandt, D. M., & Bluth, G. J. (1980). Use of top-level structure in text: Key for reading comprehension of ninth-grade students. Reading Research Quarterly, 16, 72–103. https://doi.org/10.2307/747349
Meyer, B. J. F., & Ray, M. N. (2011). Structure strategy interventions: Increasing reading comprehension of expository text. International Electronic Journal of Elementary Education, 4, 127–152.
Meyer, B. J. F., Wijekumar, K., & Lei, P. (2018). Comparative signaling generated for expository texts by 4th–8th graders: Variations by text structure strategy instruction, comprehension skill, and signal word. Reading and Writing, 31, 1937–1968. https://doi.org/10.1007/s11145-018-9871-4
Millis, K. K., King, A., & Kim, H.-J. J. (2000). Updating situation models from descriptive texts: A test of the situational operator model. Discourse Processes, 30, 201–236. https://doi.org/10.1207/S15326950dp3003_1
Minguela, M., Solé, I., & Pieschl, S. (2015). Flexible self-regulated reading as a cue for deep comprehension: Evidence from online and offline measures. Reading and Writing, 28, 721–744. https://doi.org/10.1007/s11145-015-9547-2
Mirman, D., Dixon, J. A., & Magnuson, J. S. (2008). Statistical and computational models of the visual world paradigm: Growth curves and individual differences. Journal of Memory and Language, 59, 475–494. https://doi.org/10.1016/j.jml.2007.11.006
National Assessment Governing Board. (2019). The 2019 NAEP reading framework. National Assessment Governing Board.
O'Reilly, T., & McNamara, D. S. (2007). Reversing the reverse cohesion effect: Good texts can be better for strategic, high-knowledge readers. Discourse Processes, 43, 121–152. https://doi.org/10.1080/01638530709336895
Organisation for Economic Co-operation and Development (OECD).(2021). 21st-century readers: Developing literacy skills in a digital world. OECD Publishing.
Ozuru, Y., Dempsey, K., & McNamara, D. S. (2009). Prior knowledge, reading skill, and text cohesion in the comprehension of science texts. Learning and Instruction, 19, 228–242. https://doi.org/10.1016/j.learninstruc.2008.04.003
Pastötter, B., & Bäuml, K.-H. (2014). Retrieval practice enhances new learning: the forward effect of testing. Frontiers in Psychology, Article 5. https://doi.org/10.3389/fpsyg.2014.00286
Patterson, A., Roman, D., Friend, M., Osborne, J., & Donovan, B. (2018). Reading for meaning: The foundational knowledge every teacher of science should have. International Journal of Science Education, 40, 291–307. https://doi.org/10.1080/09500693.2017.1416205
Penttinen, M., Anto, E., & Mikkilä-Erdmann, M. (2013). Conceptual change, text comprehension and eye movements during reading. Research in Science Education, 43, 1407–1434. https://doi.org/10.1007/s11165-012-9313-2
Priebe, S. J., Keenan, J. M., & Miller, A. C. (2012). How prior knowledge affects word identification and comprehension. Reading and Writing, 25, 131–149. https://doi.org/10.1007/s11145-010-9260-0
Pyle, N., Vasquez, A. C., Lignugaris/Kraft, B., Gillam, S. L., Reutzel, D. R., Olszewski, A., Segura, H., Hartzheim, D., Laing, W., & Pyle, D. (2017). Effects of expository text structure interventions on comprehension: A meta-analysis. Reading Research Quarterly, 52, 469–501. https://doi.org/10.1002/rrq.179
Rapp, D. N., Broek, P. v. d., McMaster, K. L., Kendeou, P., & Espin, C. A. (2007). Higher-order comprehension processes in struggling readers: A perspective for research and intervention. Scientific Studies of Reading, 11, 289–312. https://doi.org/10.1080/10888430701530417
Rawson, K. A. (2015). The status of the testing effect for complex materials: Still a winner. Educational Psychology Review, 27, 327–331. https://doi.org/10.1007/s10648-015-9308-4
Ray, M. N., & Meyer, B. J. F. (2011). Individual differences in children’s knowledge of expository text structures: A review of literature. International Electronic Journal of Elementary Education, 4, 67–82.
Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124, 372–422. https://doi.org/10.1037/0033-2909.124.3.372
Richter, J., Scheiter, K., & Eitel, A. (2016). Signaling text-picture relations in multimedia learning: A comprehensive meta-analysis. Educational Research Review, 17, 19–36. https://doi.org/10.1016/j.edurev.2015.12.003
Richter, J., Scheiter, K., & Eitel, A. (2018). Signaling text–picture relations in multimedia learning: The influence of prior knowledge. Journal of Educational Psychology, 110, 544-560. https://doi.org/10.1037/edu0000220
Roediger, H. L., & Karpicke, J. D. (2006a). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1, 181–210. https://doi.org/10.1111/j.1745-6916.2006.00012.x
Roediger, H. L., & Karpicke, J. D. (2006b). Test-enhanced learning:Taking memory tests improves long-term retention. Psychological Science, 17, 249–255. https://doi.org/10.1111/j.1467-9280.2006.01693.x
Roehling, J. V., Hebert, M., Nelson, J. R., & Bohaty, J. J. (2017). Text structure strategies for improving expository reading comprehension. The Reading Teacher, 71, 71–82. https://doi.org/10.1002/trtr.1590
Roelle, J., & Berthold, K. (2017). Effects of incorporating retrieval into learning tasks: The complexity of the tasks matters. Learning and Instruction, 49, 142–156. https://doi.org/10.1016/j.learninstruc.2017.01.008
Roelle, J., & Nückles, M. (2019). Generative learning versus retrieval practice in learning from text: The cohesion and elaboration of the text matters. Journal of Educational Psychology, 111, 1341–1361. https://doi.org/10.1037/edu0000345
Rowland, C. A. (2014). The effect of testing versus restudy on retention: A meta-analytic review of the testing effect. Psychological bulletin, 140, 1432–1463. https://doi.org/10.1037/a0037559
Sackett, G. P., Holm, R., Crowley, C., & Henkins, A. (1979). A FORTRAN program for lag sequential analysis of contingency and cyclicity in behavioral interaction data. Behavior Research Methods & Instrumentation, 11, 366–378. https://doi.org/10.3758/BF03205679
Salmerón, L., Naumann, J., García, V., & Fajardo, I. (2017). Scanning and deep processing of information in hypertext: an eye tracking and cued retrospective think-aloud study. Journal of Computer Assisted Learning, 33, 222–233. https://doi.org/10.1111/jcal.12152
Schmitz, A., Gräsel, C., & Rothstein, B. (2017). Students’ genre expectations and the effects of text cohesion on reading comprehension. Reading and Writing, 30, 1115–1135. https://doi.org/10.1007/s11145-016-9714-0
Scheiter, K., & Eitel, A. (2015). Signals foster multimedia learning by supporting integration of highlighted text and diagram elements. Learning and Instruction, 36, 11–26. https://doi.org/10.1016/j.learninstruc.2014.11.002
Schnotz, W., & Wagner, I. (2018). Construction and elaboration of mental models through strategic conjoint processing of text and pictures. Journal of Educational Psychology, 110, 850–863. https://doi.org/10.1037/edu0000246
Schüler, A. (2017). Investigating gaze behavior during processing of inconsistent text-picture information: Evidence for text-picture integration [Article]. Learning and Instruction, 49, 218–231. https://doi.org/10.1016/j.learninstruc.2017.03.001
Simonsmeier, B. A., Flaig, M., Deiglmayr, A., Schalk, L., & Schneider, M. (2022). Domain-specific prior knowledge and learning: A meta-analysis. Educational Psychologist, 57, 31–54. https://doi.org/10.1080/00461520.2021.1939700
Sharon, A. J., & Baram-Tsabari, A. (2020). Can science literacy help individuals identify misinformation in everyday life? Science Education, 104, 873-894. https://doi.org/10.1002/sce.21581
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data Analysis: Modeling change and event occurrence. Oxford University Press.
Snow, C. E. (2002). Reading for understanding: Toward a R&D program in reading comprehension. RAND.
Spencer, M., Gilmour, A. F., Miller, A. C., Emerson, A. M., Saha, N. M., & Cutting, L. E. (2019). Understanding the influence of text complexity and question type on reading outcomes. Reading and Writing, 32, 603–637. https://doi.org/10.1007/s11145-018-9883-0
Stevens, E. A., Vaughn, S., House, L., & Stillman-Spisak, S. (2020). The effects of a paraphrasing and text structure intervention on the main idea generation and reading comprehension of students with reading disabilities in Grades 4 and 5. Scientific Studies of Reading, 24, 365–379. https://doi.org/10.1080/10888438.2019.1684925
Stárková, T., Lukavský, J., Javora, O., & Brom, C. (2019). Anthropomorphisms in multimedia learning: Attract attention but do not enhance learning? Journal of Computer Assisted Learning, 35, 555-568. https://doi.org/10.1111/jcal.12359
Strukelj, A., Scheiter, K., Nyström, M., & Holmqvist, K. (2016). Exploring the lack of a disfluency effect: Evidence from eye movements. Metacognition and Learning, 11, 71–88. https://doi.org/10.1007/s11409-015-9146-2
Sung, Y.-T., Chang, T.-H., Lin, W.-C., Hsieh, K.-S., & Chang, K.-E. (2016). CRIE: An automated analyzer for Chinese texts. Behavior Research Methods, 48, 1238–1251. https://doi.org/10.3758/s13428-015-0649-1
Sung, Y.-T., Wu, M.-D., Chen, C.-K., & Chang, K.-E. (2015). Examining the online reading behavior and performance of fifth-graders: Evidence from eye-movement data. Frontiers in psychology, 6, Article 665. https://doi.org/10.3389/fpsyg.2015.00665
Titz, J., Scholz, A., & Sedlmeier, P. (2018). Comparing eye trackers by correlating their eye-metric data. Behavior Research Methods, 50, 1853–1863. https://doi.org/10.3758/s13428-017-0954-y
Tsai, M.-J., Wu, A.-H., Bråten, I., & Wang, C.-Y. (2022). What do critical reading strategies look like? Eye-tracking and lag sequential analysis reveal attention to data and reasoning when reading conflicting information. Computers & Education, 187, Article 104544. https://doi.org/10.1016/j.compedu.2022.104544
van den Broek, P., Bohn-Gettler, C. M., Kendeou, P., Carlson, S., & White, M. J. (2011). When a reader meets a text: The role of standards of coherence in reading comprehension. In M. T. McCrudden, J. P. Magliano, & G. Schraw (Eds.), Text relevance and learning from text. (pp. 123–139). IAP Information Age Publishing.
van Dijk, T. A., & Kintsch, W. (1983). Strategies of discourse comprehension. Academic Press.
van Gog, T., & Jarodzka, H. (2013). Eye tracking as a tool to study and enhance cognitive and metacognitive processes in computer-based learning environments. In R. Azevedo & V. Aleven (Eds.), International Handbook of Metacognition and Learning Technologies. Springer. https://doi.org/10.1007/978-1-4419-5546-3_10
van Gog, T., Paas, F., & Van Merriënboer, J. J. G. (2005). Uncovering expertise-related differences in troubleshooting performance: Combining eye movement and concurrent verbal protocol data. Applied Cognitive Psychology, 19, 205–221. https://doi.org/10.1002/acp.1112
van Gog, T., Paas, F., van Merriënboer, J. J. G., & Witte, P. (2005). Uncovering the problem-solving process: Cued retrospective reporting versus concurrent and retrospective reporting. Journal of Experimental Psychology: Applied, 11, 237–244. https://doi.org/10.1037/1076-898x.11.4.237
van Gog, T., & Sweller, J. (2015). Not new, but nearly forgotten: The testing effect decreases or even disappears as the complexity of learning materials increases. Educational Psychology Review, 27, 247–264. https://doi.org/10.1007/s10648-015-9310-x
van Silfhout, G., Evers-Vermeul, J., & Sanders, T. (2015). Connectives as processing signals: How students benefit in processing narrative and expository texts. Discourse Processes, 52, 47–76. https://doi.org/10.1080/0163853X.2014.905237
Voss, J. F., & Silfies, L. N. (1996). Learning from history text: The interaction of knowledge and comprehension skill with text structure. Cognition and Instruction, 14, 45–68. https://doi.org/10.1207/s1532690xci1401_2
Wallace, C. S. (2004). Framing new research in science literacy and language use: Authenticity, multiple discourses, and the “Third Space”. Science Education, 88, 901–914. https://doi.org/10.1002/sce.20024
Wang, T.-N., Jian, Y.-C., Wu, C.-J., & Li, P. (2022). Science reading and self-regulated learning: Evidence from eye movements of middle-school readers. The Journal of Educational Research, 115, 11–24. https://doi.org/10.1080/00220671.2021.2012637
Williams, J. P. (2018). Text structure instruction: The research is moving forward. Reading and Writing, 31, 1923–1935. https://doi.org/10.1007/s11145-018-9909-7
Williams, J. P., Kao, J. C., Pao, L. S., Ordynans, J. G., Atkins, J. G., Cheng, R., & DeBonis, D. (2016). Close analysis of texts with structure (CATS): An intervention to teach reading comprehension to at-risk second graders. Journal of Educational Psychology, 108, 1061–1077. https://doi.org/10.1037/edu0000117
Wissman, K. T., Rawson, K. A., & Pyc, M. A. (2011). The interim test effect: Testing prior material can facilitate the learning of new material. Psychonomic Bulletin & Review, 18, 1140–1147. https://doi.org/10.3758/s13423-011-0140-7
Wright, K. L., Franks, A. D., Kuo, L.-J., McTigue, E. M., & Serrano, J. (2016). Both theory and practice: Science literacy instruction and theories of reading. International Journal of Science and Mathematics Education, 14, 1275–1292. https://doi.org/10.1007/s10763-015-9661-2
Wylie, J., & McGuinness, C. (2004). The interactive effects of prior knowledge and text structure on memory for cognitive psychology texts. British Journal of Educational Psychology, 74, 497–514. https://doi.org/10.1348/0007099042376418
Yang, C., Chew, S.-J., Sun, B., & Shanks, D. R. (2019). The forward effects of testing transfer to different domains of learning. Journal of Educational Psychology, 111, 809–826. https://doi.org/10.1037/edu0000320
Yang, C., Potts, R., & Shanks, D. R. (2017). The forward testing effect on self-regulated study time allocation and metamemory monitoring. Journal of Experimental Psychology: Applied, 23, 263–277. https://doi.org/10.1037/xap0000122
Yang, C., Potts, R., & Shanks, D. R. (2018). Enhancing learning and retrieval of new information: a review of the forward testing effect. npj Science of Learning, 3. Article 8. https://doi.org/10.1038/s41539-018-0024-y
Yang, F.-Y., Huang, R.-T., & Tsai, I. J. (2016). The effects of epistemic beliefs in science and gender difference on university students’ science-text reading: An eye-tracking study. International Journal of Science and Mathematics Education, 14, 473–498. https://doi.org/10.1007/s10763-014-9578-1
Yang, F.-Y., Tsai, M.-J., Chiou, G.-L., Lee, S. W.-Y., Chang, C.-C., & Chen, L.-L. (2018). Instructional suggestions supporting science learning in digital environments based on a review of eye tracking studies. Journal of Educational Technology & Society, 21, 28–45.
Yi, W. (2022). Processing of novel L2 compounds across repeated exposures during reading: A growth curve analysis. Applied Psycholinguistics, 43, 551–579. https://doi.org/10.1017/S0142716422000017
Yore, L., Bisanz, G. L., & Hand, B. M. (2003). Examining the literacy component of science literacy: 25 years of language arts and science research. International Journal of Science Education, 25, 689–725. https://doi.org/10.1080/09500690305018
Zander, S., Wetzel, S., Kühl, T., & Bertel, S. (2017). Underlying processes of an inverted personalization effect in multimedia learning - An eye-tracking study. Frontiers in Psychology, 8(DEC), Article 2202. https://doi.org/10.3389/fpsyg.2017.02202
Zhang, D., Hyönä, J., Cui, L., Zhu, Z., & Li, S. (2019). Effects of task instructions and topic signaling on text processing among adult readers with different reading styles: An eye-tracking study. Learning and Instruction, 64, Article 101246. https://doi.org/10.1016/j.learninstruc.2019.101246
Zimmerman, B. J. (2013). From cognitive modeling to self-regulation: A social cognitive career path. Educational Psychologist, 48, 135–147. https://doi.org/10.1080/00461520.2013.794676