手寫與數位筆記對論文閱讀理解成效之研究

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(1). Department of English, College of Liberal Arts. National Taiwan Normal University Master’s Thesis. Notes-worthy? Effects of Longhand vs Laptop Note-taking on Reading Comprehension of Research Papers. Hung, Yu-Tzu. 109. 1. January 2020.

(2) . ACKNOWLEDGEMENTS “Though the mountains be shaken and the hills be removed, yet my unfailing love for you will not be shaken nor my covenant of peace be removed,” says the LORD, who has compassion on you. (Isaiah 54:10) Writing the graduate thesis was relishing a journey of exploration, discovery and skepticism about not only knowledge but also myself. Sometimes, things got too hard to laugh it through but glad the people I met made it not a bit, but a lot easier to bear with. And most importantly, to enjoy it and try to learn from it. I would like to express my gratitude, first, to my advisor, Prof. Yeu-Ting Liu, who guided me through this eye-opening journey. He enlightened me with profound advice, encouraged me to think outside the box and cultivate my critical thinking whenever we had a meeting. Moreover, he told me to never overlook my potential. He encouraged me to set a high standard and challenge my ability. Above all, he never gave up on me. His attitude not only help me through the thesis but made my mind stronger throughout these years. Secondly, my thankfulness goes to my committee members, Prof. Hung-Chun Wang from NTNU and Prof. Ya-Chen Chien from NTUE. I sincerely appreciate their time and efforts in reading through my thesis. Their kind suggestions took me a step further in understanding my topic during the oral defense. Their insightful comments have also provided strong aid in helping me revise the thesis. Next, special thanks go to the participants in the current study. Without their nice cooperation and dedicating participation, the study would not have been completed so smoothly.. i.

(3) . In addition, I would like to show my gratitude to my dear friends in graduate school. Sailing in the academic world wasn’t easy, but thanks to the friends in class, I was never alone. Special thanks go to Gloria Hung, who walked by me and encouraged me through this amazing journey; to Annie Lu, who acted as my secretary and lent a helping hand whenever I was in need; to Kyle Lai, who proofread my thesis and provided thoughtful advice; to Charlene Tsai, who set a good example with selfdiscipline and perseverance; and to Aletha Alfarania, Maddie Chen, Wesley Yin and Edward Chin, who always treated me so well like their little sister. Finally, I couldn’t show my appreciation enough to my family. Their unconditional love, expectation and belief in me were the reasons I could finish the thesis. My father’s full support, my mother’s warm encouragement and my sister’s treating me to a meal whenever I was down accompanied me through this tough journey. This thesis is especially dedicated to my father, who fully believe in me and during the journey, taught me the true meaning of “Love is something more stern and splendid than mere kindness.”. ii.

(4) . ——. 26. Leximancer. Concept. Theme. iii.

(5) . ABSTRACT Existing research has established that the act of note-taking can theoretically benefit both L1 and L2 students by increasing the information recalled, enhancing comprehension and leading to better later performance. However, these studies were mostly done in L1 lecture settings where participants listened and took notes. In addition, with the improvement of technology, more students start to choose laptop over pen and paper to take notes. To optimize the pedagogical value of taking notes during learning, it is important to understand how L2 learners’ note-taking can affect their reading comprehension. The current study was therefore set out to investigate the effects of different note-taking modalities (laptop versus longhand) on L2 reading comprehension of 26 Taiwanese EFL learners and how their note contents differ. All participants read through a research paper while took notes with laptops or longhand. They then completed a reading comprehension test with 20 questions (10 factual questions and 10 conceptual questions). The results showed no significance difference on the reading comprehension between participants who took notes with different modalities. Moreover, the word count of the two notes were not significantly different. However, with Leximancer concept-mapping system, the contents of the two notes showed salient differences in their key idea units (Concepts and Themes). Laptop notes were found to be more similar to the original reading text. On the other hand, longhand participants took down fewer key concepts but had comparable comprehension outcome with their laptop counterparts.. Key words: note-taking modality, educational technology, reading comprehension. iv.

(6) . TABLE OF CONTENTS .............................................................................................................................. iii ABSTRACT ................................................................................................................. iv TABLE OF CONTENTS ............................................................................................. v LIST OF TABLES .................................................................................................... viii LIST OF FIGURES .................................................................................................... ix CHAPTER 1 INTRODUCTION ................................................................................ 1 1.1 Background and Motivation ................................................................................ 1 1.2 Rationale of the Study.......................................................................................... 4 1.3 Scope of the Study ............................................................................................... 5 1.4 Significance of the Study ..................................................................................... 6 1.5 Research Questions .............................................................................................. 6 1.6 Organization of the Study .................................................................................... 7 CHAPTER 2 LITERATURE REVIEW .................................................................... 8 2.1 Theoretical Accounts on the Functions of Note-taking ....................................... 8 2.1.1 Functions of note-taking in reading. ............................................................. 9 2.2 Theoretical Accounts on Modality Effects on Handwriting vs. Typing............. 11 2.2.1 Kinesthetic engagement. ............................................................................. 12 2.2.2 Attention and distraction. ............................................................................ 14 2.3 Empirical Studies of Longhand vs Laptop Note-taking .................................... 15. v.

(7) . 2.3.1 Empirical studies of longhand vs laptop note-taking effects on lecture comprehension. .................................................................................................... 16 2.3.2 Empirical study of longhand vs laptop note-taking effects on reading comprehension. .................................................................................................... 25 2.3.3 General findings from empirical studies of longhand vs laptop note-taking. .............................................................................................................................. 28 2.4 Major Findings and Research Gap ..................................................................... 33 CHAPTER 3 METHODOLOGY ............................................................................. 35 3.1 Participants......................................................................................................... 36 3.2 Material and Design ........................................................................................... 37 3.2.1 Reading Source ........................................................................................... 37 3.2.2 Design. ........................................................................................................ 39 3.3 Instruments......................................................................................................... 40 3.3.1 Note-taking Instruments.............................................................................. 40 3.3.2 Reading Comprehension Test ..................................................................... 41 3.3.3 Leximancer System ..................................................................................... 43 3.4 Procedures of the Study ..................................................................................... 45 3.5 Data Analysis ..................................................................................................... 46 3.5.1 Analysis of comprehension test. ................................................................. 46 3.5.2 Analysis of note content. ............................................................................. 47 3.6 Summary and Hypothesis .................................................................................. 47. vi.

(8) . CHAPTER 4 RESULTS ............................................................................................ 49 4.1 Which kind of note-taking modality (i.e., longhand or laptop) leads to better reading comprehension? .......................................................................................... 50 4.2 Are there any quantitative (i.e., word count) and qualitative (i.e., idea units) differences between longhand and laptop notes? If so, what are they? ................... 53 4.2.1 Quantitative differences between longhand and laptop notes..................... 53 4.2.2 Qualitative differences between longhand and laptop notes: Leximancer content analysis. ................................................................................................... 55 4.3 Summary of the Quantitative and Qualitative Results ....................................... 61 CHAPTER 5 DISCUSSION ..................................................................................... 62 5.1 Note-taking and Reading Comprehension Test Performance ............................ 62 5.2 Differences between laptop notes and longhand notes. ..................................... 65 CHAPTER 6 CONCLUSION ................................................................................... 68 6.1 Summary of the Major Findings ........................................................................ 68 6.2 Pedagogical Implications ................................................................................... 69 6.3 Limitations of the Study and Suggestions for Future Research ......................... 70 REFERENCES........................................................................................................... 73 APPENDIX A: Comprehension Questions ............................................................. 84. vii.

(9) . LIST OF TABLES Table 1. Examples of Each Question Type Used in Study 3 of Mueller and Oppenheimer’s Research (2014) ...................................................................18 Table 2. Summary of the results of relative studies .....................................................29 Table 3. Information of the Reading Material ............................................................38 Table 4. Information of the Participants .....................................................................40 Table 5. The procedures of the study ......................................................................... 46 Table 6. Descriptive statistics of the participants’ performance based on note-taking modality and question type .............................................................................52 Table 7. MANOVA Inferential statistics of participants’ performance based on notetaking modality and question type .................................................................53 Table 8. Note-taking modality and notes word count .................................................54 Table 9. Pearson Product-Moment Correlation of word count and test performance ....................................................................................................54 Table 10. Summary of the present research findings..................................................67. viii.

(10) . LIST OF FIGURES Figure 1. Loose leaf paper with embossed lines used in the present study .................41 Figure 2. A blank Microsoft Word document used in the present study .....................41 Figure 3. An example of Leximancer processing .......................................................43 Figure 4. Leximancer map: Theme circles of the study text .......................................56 Figure 5. Leximancer map: Theme circles of the laptop notes................................... 57 Figure 6. Leximancer map: Theme circles of the longhand notes .............................57 Figure 7. Leximancer map: Concepts of the study text ...............................................58 Figure 8. Leximancer map: Concepts of the laptop notes ..........................................59 Figure 9. Leximancer map: Concepts of the longhand notes ......................................60. ix.

(11) . CHAPTER 1 INTRODUCTION 1.1 Background and Motivation Imagine the daily life of graduate students. Before the class, they preview the research paper assigned for the week. They read through the paper, highlight the important points and jot down keywords in the column to help with their comprehension. Occasionally, they would logically organize their understanding of the study into notes. Some do so while reading the paper; others arrange their notes after reading the paper; and the rest simply skip the part of note-taking. Let us shift the scene to the classroom. During class, the presenter (a student or a professor) would stand in front of the class, pointing at the PowerPoint slides and explaining the content of the research paper. Meanwhile, the audience listens to the presentation and takes notes on their laptops or notebooks. The aforementioned scenes are different episodes typical of many graduate students’ study routine. There is, in fact, a common ground between these actions: note-taking. While the first scene depicts reading notes, the second describes lecture notes. Reading notes are the excerpt and the information that a learner writes or types down from a reading passage (Horwitz, 2017). In contrast, lecture notes are the recording of the information received while a learner listens to a lecture or a speech (DiVesta & Gray, 1972). There is no limitation to the form of notes; phrases, sentences, bullet points, graphic-organizers and pictures can all be considered notes (Dunkel, 1988; O’Malley & Chamot, 1985).. 1.

(12) . Previous research has established that note-taking – in particular lecture notes – can theoretically benefit students by increasing the information recalled, enhancing lecture comprehension and leading to better later performance (Barnett, Di Vesta, & Rogozinski, 1981; Di Vesta & Gray, 1972; Peper & Mayer, 1978, 1986). This effectiveness can be attributed to what is called the encoding function of note-taking (Di Vesta & Gray, 1972). When taking notes, learners may direct their attention to new materials and may link new information to what is already known (Frase, 1970; Moos & Azevedo, 2008; Trevors, Duffy, & Azevedo, 2014) by selecting, summarizing and reorganizing what is newly learned (Bonner & Holliday, 2006; Craik & Lockhart, 1972; Kiewra, 1985). While note-taking has long been investigated by educational psychologists (e.g., Armbruster, 2000; Crawford, 1925; Corey, 1935; Einstein, Morris, & Smith, 1985), previous research has focused primarily on lecture notes (Armbruster, 2000; Carrell, Dunkel, & Mollaun, 2004; Chaudron, Loschky, & Cook, 1994; Einstein, Morris & Smith, 1985; Kunkel, 2004; Peverly, Garner, & Vekaria, 2014). This research focus reflects the observation that students from elementary school to high school (or even university) tend to take lecture notes, either voluntarily or passively; they are used to listening to the teachers and jotting down important ideas as notes in class. Nonetheless, reading notes have not attracted much research interest. It is important to note that older students, university or graduate school students in particular, have more opportunities to take reading notes. Especially in graduate schools, students are usually asked to preview and understand the studies before the lesson so that fruitful classroom discussions can take place during the class.. 2.

(13) . Apart from listening to lectures, individual reading is the main resource for gaining new knowledge for learners, especially those who have received higher education. However, reading alone does not necessarily guarantee the understanding and transmission of the learning content to our long-term memory (Alptekin & Erçetin, 2010; Kintsch, 1994; Mangen, Walgermo, & Brønnick, 2013). A vast variety of reading strategies have thus been introduced to learners in order to help reading comprehension, including concept mapping, summarizing, questioning, predicting, skimming and scanning, etc. (Dole, Duffy, Roehler, & Pearson, 1991; Lau & Chan, 2003; Pressley, 1990; Salataci, 2002; Spörer, Brunstein, & Kieschke, 2009). Notetaking during reading has not been widely discussed in these studies. One reason may be that note-taking is considered a “habit”, not a strategy, of learners (Palmatier & Bennett, 1974). When reading a text, many graduate students tend to write down keywords or main ideas to assist their understanding. Especially when reading longer or more complicated texts like research papers, multiple ideas can be logically presented by using bullet points or mind maps in the reading notes. In addition to various possibilities in how the ideas can be organized in reading and lecture notes, notes can be subdivided into two categories depending on the amount of overlap between a lecture or reading passage and students’ notes: predominantly generative notes (i.e., paraphrasing, reframing, concept mapping) or predominantly non-generative notes (i.e. verbatim copying) (Kiewra, 1985). Empirical studies on lecture notes have shown that efficacy of note-taking drastically decreases when verbatim copying is applied (Mueller & Oppenheimer, 2014) and that non-verbatim generative note-taking leads to better learning outcome and learner. 3.

(14) . performance, especially on conceptual and integrative items, than verbatim notetaking (Aiken, Thomas, & Shennum, 1975; Bretzing and Kulhavy, 1979; Slotte and Lonka, 1999; Igo Bruning, & McCrudden, 2005). Whether the above insight holds true for reading notes is yet to be established. In particular, the effect of reading notes on students’ reading and learning outcomes warrants further research. In this research endeavor, the modality in which the notes are taken also needs to be considered (longhand notes vs. laptop notes). The use of laptops in higher education has bloomed. This has allowed people to take notes with efficiency and faster input speed. However, research on lecture notes has shown that laptop notes result in promoting verbatim transcription of the lecture contents (Mueller & Oppenheimer, 2014; Lalchandani & Healy, 2016), which in turn leads to shallow cognitive processing of the heard or read content. In this regard, the encoding benefits of laptop notes may be impaired. Interestingly, Mueller and Oppenheimer (2014) found out that even when undergraduate students were consciously reminded to take laptop notes in their own words, they still keep taking verbatim notes. Accordingly, as far as lecture notes are concerned, empirical evidence has suggested that longhand notes have the potency to promote generative note-taking behaviors and are hence more desirable in promoting better encoding outcomes (Mueller & Oppenheimer, 2014).. 1.2 Rationale of the Study Based on the above issues in note-taking and learning outcomes, three rationales motivate the current study. First, while the effectiveness of lecture notes is well. 4.

(15) . known and thoroughly-studied, there is a gap in educational research field on the effects of learners’ reading notes. Based on this research inadequacy, the present study intends to uncover the effects of two major types of reading notes (longhand notes and laptop notes) on reading comprehension. Second, empirical evidence regarding the relative effects of longhand and laptop notes are still not extensive, especially in the domain of reading notes. It was not until the current decade did the query about the relative efficacy of longhand and laptop notes begin to take notice by researchers, e.g., Bui, Myerson, & Hale, 2013; Mueller, & Oppenheimer, 2014; Van Hove, Vanderhoven, & Cornillie, 2017; etc. Third, within these handful of studies, due to the nature of the design, while some qualitative descriptions had been provided, the relative efficacy of longhand and laptop notes is mostly examined by quantitative data. Note-taking is a process of learning and organizing new information. Notes are visible records of how the person makes meaning of what has been covered. Thus, the present study sets out to investigate not only quantitative posttest performance but also qualitative note contents and participant perceptions.. 1.3 Scope of the Study To understand whether different modalities influence note-taking behavior and outcomes during second language (L2) reading, the present study sets out to compare longhand and laptop reading notes while students read research papers published in the their L2, in this case, English. Research papers are chosen to be the reading material for the target population/participants of this study. The reasons being that,. 5.

(16) . first, graduate students are one of the major reader populations. They are not only familiar with but are also motivated to read the research papers because research papers are closely related to graduate students’ study routine. Second, comparing to common passages, research papers consist of difficult content that is ideal for notetaking and hence provides a great testing ground to test the efficacy of reading notes. Learners have been found to undergo deeper mental processing when dealing with more difficult tasks (Oded & Walters, 2001). Since research papers are more complicated in nature and contain higher density of knowledge than common reading materials, being actively involved in reading (i.e. taking generative notes in this case) may bring exceptionally positive outcomes. . 1.4 Significance of the Study This study aims to investigate the effect of digital or longhand note-taking on the learning of research papers. The significance of this study can be examined from the pedagogical perspective. By comparing the outcomes of the quantitative posttests and qualitative notes production from different modalities (longhand versus laptop), it is hoped that the findings of the study may help professors and students understand a more effective way to read and understand research papers.. 1.5 Research Questions The present study will be set out to address the following two research questions: 1.. Which kind of note-taking modality (i.e., longhand or laptop) leads to better reading comprehension?. 6.

(17) . 2.. Are there any quantitative (i.e., word count) and qualitative (i.e., idea units) differences between longhand and laptop notes? If so, what are they?. 1.6 Organization of the Study The thesis is organized as follows. Chapter One provides an introduction to the function and general background information of both lecture notes and reading notes. The presence of note-taking on laptops is also discussed. Chapter Two will first briefly distinguish between writing longhand and typing. Literature review will then be offered about the effects of different note-taking modalities (i.e., longhand and laptop) on reading comprehension. Chapter Three describes details of the methodology in the present study. The results will be presented in Chapter Four and the discussions will be shown in Chapter Five. Finally, Chapter Six will summarize the major findings of the present study and provide further pedagogical implications.. 7.

(18) . CHAPTER 2 LITERATURE REVIEW This study investigates the effects of longhand versus laptop note-taking on L2 learners’ reading comprehension. To explore the stated research questions, the relevant literature is reviewed in this chapter, separated into five sections: Section 2.1 introduces the general functions of note-taking; Section 2.2 explores the theoretical accounts on handwriting and typing; Section 2.3 reviews empirical studies investigating effects of longhand versus laptop note-taking on comprehension measured by different test types; and finally, major findings and limitations from previous studies will be summarized in section 2.4.. 2.1 Theoretical Accounts on the Functions of Note-taking As note-taking has long been a common practice during classroom or individual learning, the functions of note-taking have been under great interest for decades among educational researchers (e.g., Armbruster, 2000; Bui, Myerson, & Hale, 2013; Di Vesta & Gray, 1972; Peverly, Garner, & Vekaria, 2014; Mueller, & Oppenheimer, 2014). The two major functions of note-taking, encoding and external storage, were first described by Di Vesta and Gray (1972). The encoding function refers to the action of note-taking as a process of subjective selections, associations and interpretations by the learners themselves, while the external storage function emphasizes the use of taken notes for later study and review purposes. In their study, positive effects on the numbers of ideas recalled were found in the results when learners took notes.. 8.

(19) . Peper and Mayer (1978) then focused on the encoding mechanism and perceived note-taking as a generative activity. This study found that meaningful and assimilative encoding only occurs under three conditions: when a) the material is received; b) meaningful prior experiences are accessible; and c) the learner actively processes those experiences while learning. As such, mere verbatim notes and text-copying do not coalesce into strong encoding results. The insights echo back to Ausubel’s (1963) subsumption theory which postulates that learning is the ability to link new knowledge back to learners’ own cognitive structures. This process creates meaningful learning and leads to better learning outcomes and better recall. Notetaking, with learners’ selecting, summarizing and inferencing new knowledge (i.e., processing the information more deeply) thus lays the foundation for meaningful learning to take place and assumes active learners as well. In short, note-taking is generally considered helpful for input interpretation, storage and retrieval in learners’ memory.. 2.1.1 Functions of note-taking in reading. To contextualize the inquiries of this study, it is important to understand the theoretical tenets of mental representations during reading (Britt, Perfetti, Sandak, & Rouet, 1999; Kintsch, 1998). Van Dijk and Kintsch’s (1983) model of information comprehension identifies and categorizes three levels of mental representation that explain how meaning is constructed in the process of reading. Surface structure refers to the verbatim memory of actual words, phrases and sentences. The text-based level emphasizes the semantic content and structure of the text. When learners link and. 9.

(20) . infer text-based representation to their prior knowledge, this is known as the situational model. While the text-based level of understanding allows learners to answer factual questions, the situation model is indispensable for casual inferencing and successful comprehension of a text, which are the ultimate goals of reading (Morrow, 2008; Zwann & Brown, 1996). To form a mental representation of situations that are implied by a text, learners need to do more than just read passively. One way to engage more actively with a text is by taking non-verbatim generative notes. Results from previous research support such claim (Bohay, Blakely, Tamplin, & Radvansky, 2011; Slotte & Lonka, 1999). The process of taking extensive high-quality notes depends, in fact, on the learners’ own inference-making. It demands that readers not only devote their attention to the reading of materials but also dedicate time and effort to consciously think about what they are reading (Piolat, Olive & Kellogg, 2005). When they take non-verbatim notes in their own words, they elaborate more on the text, use greater metal organization and include their prior knowledge to help assimilate new information (Einstein, Morris, & Smith, 1985). Therefore, even without reviewing their notes, higher-quality (non-verbatim) note-taking learners are reported to perform better, especially on tasks such as text evaluation and comparison, in which a representation of the situation model is required (Slotte & Lonka, 1999). Van Dijk and Kintsch’s three levels of representation (1983) contribute separately to reading comprehension. The importance of the situation model for these two aspects has especially been discussed (Morrow, 2008; Perfetti, Landi, & Oakhill, 2005). In addition, the encoding function of note-taking (Di Vesta & Gray, 1972) has. 10.

(21) . been generally reported to lead to deeper understanding and memory, as with the situation model (Bohay et al., 2011; Slotte & Lonka, 1999). With the concrete base of the effectiveness of note-taking, the current study aims to take a step further and investigate the influence of taking text notes via different modalities, i.e., longhand versus laptop.. 2.2 Theoretical Accounts on Modality Effects on Handwriting vs. Typing Before going into the more detailed functions and effects of text note-taking, this section will discuss the recent theoretical currents of handwriting and typing. In the past few decades, computers, laptops, tablets and smart phones have risen to dominance in terms of note-taking media, and research on whether handwriting can be replaced by typewriting has attracted great interest. Despite the fact that it has long been recognized that there are perceptual differences between reading handwritten and typed words (Corcoran & Rouse, 1970; Ford & Banks, 1977), what the perceptual processes actually are, and how they influence reading outcomes have not yet reached an agreement (Barnhart & Goldinger, 2010; Nakamura, Kuo, Pegado, Cohen, Tzeng, & Dehaene, 2012; Perea, Gil-López, Beléndez, & Carreiras, 2016). On the contrary, there is a greater consensus on the findings of production in these two different modalities. Handwriting is more than just an archaic tool of learning and recording; it has been proven to hold a positive effect over typing on written text comprehension (Klatzky, Lederman, & Mankinen, 2005; Mueller & Oppenheimer, 2014).. 11.

(22) . While there are handful studies on the effects of longhand notes versus computer notes, theoretical accounts onto notes taking on these two modalities are missing (Mueller & Oppenheimer, 2014). Nevertheless, insights obtained from the literature addressing possible effects of longhand and typewriting output can still lay the ground for the inquiries for the present study. Fundamental differences of two modalities will be introduced with supportive findings in the ensuing subsections (Mangen & Velay, 2010).. 2.2.1 Kinesthetic engagement. While handwriting requires unique depiction and reproduction of each letter, typing contains much less kinesthetic engagement. The physical movements of typing are not directly related to the letter shape and therefore no graphomotor component is involved. As recent psychological research has shown that hand-brain relationship and haptic experiences are important to text acquisition, it would be no surprise that typing (which lacks motor programs that provide memory traces) may impact learning outcomes, especially with regards to graphic shapes (Kiefer, Schuler, Mayer, Trumpp, Hille, & Sachse, 2015; Klatzky et al., 2005). Only the process of handwriting creates sensory-motor memory trace, which is the meaningful coupling of perception and action. When learners write, additional information of the shape of letters is developed and may facilitate later recall (Kiefer et al, 2015). This again echoes back to the claim that the perception of written languages and motor action are closely related (Smoker, Murphy, & Rockwell, 2009).. 12.

(23) . As visual processing of graphic shapes is salient to efficient reading, the studies on the effects of handwriting and typing production center on quite similar issues, namely letter recognition and word recall. For instance, Longcamp, Zerbato-Poudou and Velay (2005) investigated children’s memory of letters after an exercise involving the copying of the alphabet by either handwriting or typing. The results showed that the children who went through handwriting training had a significant increase in letter recognition. This suggests that the meaningful coupling between action and perception during handwriting aids memory retention. Based on this study, extensive research has explored adults’ memory and recognition of non-letters by looking at images of the brain taken via functional magnetic resonance imaging (fMRI) during the process of recognition (Longcamp, Boucard, Gilhodes, Anton, Roth, Nazarian, & Velay, 2008). Better and longer-lasting recognition of the new letters was found in the group that had learned by handwriting. On top of that, greater activity in the left Broca’s area (which is related to various linguistic functions) was found when recognizing letters written by hand rather than typed. Motor knowledge gained by handwriting thus seems to suggest better outcomes for learning individual characters. Similar results have been found in fMRI images of pre-literate children’s brains in the process of word recognition (James & Engelhardt, 2012). Only those who had handwritten—not those who had typed or traced letters—showed recruitment of reading components in the brain when they perceived the letters. The findings suggest that handwriting is important for letter processing that may later determine later successful reading comprehension.. 13.

(24) . 2.2.2 Attention and distraction. Another major difference between these two text-production modalities lies with focus and attention. Learners concentrate on the tip of the pen when they handwrite, whereas during typewriting, their attention is divided into two parts: the motor space (e.g. the keyboard) and the visual space (e.g. the screen) (Mangen & Velay, 2010). While this may not be true for professional typists who do not need to look at the keyboard during typing, there is a lack of research on this fundamental issue. Furthermore, the use of a laptop while learning has been found to increase the chance of distraction (Gipson, Kim, Shin, Kitts, & Maneta, 2017; Kay & Lauricella, 2011; Yamamoto, 2007). Students nowadays use laptops in class or during selfstudying for mainly two purposes: taking notes or searching for related information. While most students claim that they learn better with laptops, researchers have found that laptops in class can distract both users and nearby classmates, and may hinder learning (Fried, 2008; Sana, Weston, & Cepeda, 2013; Skolnick & Puzo, 2008; Wurst, Smarkola, & Gaffney, 2008). With internet access available on most campuses, students can easily switch between online news, chat windows and their email accounts when they take notes. In their study on note-taking in different media environments, Lin and Bigenho (2011) found that multitasking not only distracted students from the learning tasks but also made note-taking itself yet another distraction rather than an assistance. Moreover, when there are too many distractions from multimedia (which is a common case of using laptops), learners may be overwhelmed and experience difficulty in using cognitive strategies such as notetaking to help with their understanding and memorizing.. 14.

(25) . Regarding the influence of handwriting and typing on text comprehension and memory, two competing hypotheses are therefore postulated. On the one hand, handwriting creates sensory-motor memory traces that benefit learners on letter-level and word-level acquisition. On the other hand, the convenience and efficiency of typing may suggest richer recordings and longer production. In short, the better quality of handwriting and the larger quantity of typewriting are on either side of the scales of text comprehension. While both modalities have their supporters, the issue under debate has recently extended to the field of note-taking.. 2.3 Empirical Studies of Longhand vs Laptop Note-taking Studies directly assessing the effects of longhand versus laptop note-taking are still very limited (e.g., Bui et al., 2013; Horwitz, 2017; Mueller & Oppenheimer, 2014). Within these handful studies, most of them focus primarily on lecture comprehension; except for only one study to date considering note-taking impact on reading comprehension (Horwitz, 2017). Therefore, it is still too abrupt to draw conclusions regarding test performances of taking laptop versus longhand notes. In order to build a more thorough understanding of the stated issue, detailed review of tasks and results of studies carried out in lecture conditions will first be presented in the following section. Mueller and Oppenheimer’s (2014) pioneering study directly addressing the issue of longhand and laptop note-taking during lecture will be reviewed, followed by related studies about note-taking strategies (Bui et al., 2013) and note-taking medium preferences (Kirkland, 2016). Afterwards, Horwitz’s (2017) study on students’ individual reading will be reviewed in details. Methodology and. 15.

(26) . findings from lecture condition and reading condition research will then be compared in order to set the stage for the present study.. 2.3.1 Empirical studies of longhand vs laptop note-taking effects on lecture comprehension. 2.3.1.1 Mueller and Oppenheimer (2014). In their three-part research of The Pen Is Mightier Than the Keyboard: Advantages of Longhand Over Laptop Note-taking (Mueller & Oppenheimer, 2014), Muller and Oppenheimer intended to explore the potential differences of longhand and laptop note-taking, an issue that had hardly been directly addressed before. The first and the second studies probed into the encoding function while the third study explored the external-storage function of note-taking (Di Vesta & Gray, 1972). The manner in which different modalities affect lecture comprehension and academic performance was the focus of the research. In the first study, Mueller and Oppenheimer (2014) were interested in natural note-taking habits and their effect on class lectures. Participants were 65 students from the Princeton University subject pool. Five TED talks were chosen as the materials based on their length (slightly over 15 minutes) and topics (interesting but uncommon). Participants were given either a laptop or a notebook and were asked to take notes as if they were in class. They then took reading span tasks and distractor tasks for approximately 30 minutes. Afterwards, they completed the posttest, including factual-recall questions (e.g., “Which of these is not the name of an algorithm the speaker mentioned in the talk?”) and conceptual-application questions. 16.

(27) . (e.g., “Does the speaker think division of labor by the sexes is beneficial? What evidence does he present to support his viewpoint?”). Finally, a demographic overview was taken by measuring participants’ personal information (e.g. GPA and SAT scores) and their perceptions and habits of note-taking (e.g., “Do you normally take notes in class on your laptop or in a notebook? Why?”) Regarding the performance, results showed that both groups performed equally well on factual recall. However, on conceptual-application questions, laptop note takers performed significantly worse than those using notebooks. In the analysis of note contents, longhand note-taking resulted in significantly fewer words. An n-gram program was used to measure the overlap between note contents and lecture transcript. It was found that with various word chunks (3-grams, 2-grams and 1grams) as the measure, all of them showed significantly more verbatim overlap in laptop notes. In general, participants who took more notes and whose notes contained less verbatim overlap performed better. A second study was therefore conducted to see if explicit instructions could prevent verbatim note-taking. One hundred and fifty-one college students were divided into three groups, namely longhand, laptop-intervention and laptopnonintervention groups. Apart from the fact that the laptop-intervention group was orally reminded not to transcribe the lecture but to take notes in their own words, materials and procedures of the experiment were similar to those in the first study. The results replicated the findings in the first study. Longhand participants beat laptop-nonintervention participants on conceptual questions while no significant differences were found in factual recalls. Participants with more notes also performed. 17.

(28) . better in the posttest. In addition, the intervention of a verbal reminder did not prevent verbatim transcription in laptop note-taking at all. No reduction of verbatim overlap was shown in the laptop-intervention group. Table 1 Examples of Each Question Type Used in Study 3 General Type. Question Type. Example. Factual. Fact. What areas in the brain automatically control the rate of breathing?. Seductive detail. About how large is the surface area of the lungs' alveoli?. Conceptual. Concept. Gas exchange occurs in a part of the human respiratory system called the alveoli. How does the process of gas exchange work?. Inference. If a person's epiglottis were not working properly, what would be likely to happen?. Application. Most cars that burn gasoline have an emissions control system that includes a component called an oxygen sensor, which functions in a similar way to the system in the human body that can trigger involuntary breathing. How does this emissions control system work?. Since laptop note-taking had resulted in more notes in any case, the third study intended to investigate the external-storage function by providing an opportunity for learners to review their notes. Materials were recordings of four prose passages adapted from Butler (2010). One hundred and nine college students were asked to take notes on the lecture with either a laptop or a notebook. The participants were also 18.

(29) . informed that they would be tested on the lecture a week later. Before the posttest, half of the participants were given 10 minutes to study their notes while others took the test immediately. The posttest included five types of tasks adapted from Butler (2010): facts, seductive details (i.e., interesting but trivial information; Garner, Gillingham, & White, 1989), concepts, same-domain inferences (inferences), and new-domain inferences (applications) (Mueller & Oppenheimer, 2014). Examples of different question types were provided in Table 1. Finally, participants answered demographic measures after the comprehension posttest. To analyze the results, performance on questions of facts and seductive details were collapsed into the “factual” measure while performance on questions of concepts, inferences and applications were collapsed into “conceptual” measure. There were no differences between laptop or longhand note-taking when the learners were not given a chance to review their notes. However, the longhand-study group outperformed other groups in all test types. While more notes generally suggested better performance, the review of laptop notes (with more words and information) surprisingly led to worse performance on factual questions than the review of longhand notes (with fewer words). One possible reason may be that more mental efforts were engaged in the process of longhand note talking, therefore the review of notes may have been more efficient before the posttest. However, the results should be treated with caution, as it is limited to the condition where there was a longer delay between input processing and the comprehension test.. 19.

(30) . 2.3.1.2 Bui, Myerson, & Hale (2013). In their three-part study Note-Taking with Computers: Exploring Alternative Strategies for Improved Recall, Bui, Myerson and Hale (2013) explored how working memory, note-taking instructions and modalities affected lecture recall performances on an immediate posttest (Experiment 1) and on delayed tests when participants took the test directly (Experiment 2) and when they were allowed to study their notes (Experiment 3). In the first experiment, participants were 80 undergraduate students. Besides the main note-taking experiment, they underwent a reading span task and a lexical decision task, assessing their working memory ability and processing speed respectively. While listening to an 11-minute lecture, they were assigned to take either computer or longhand notes for an upcoming test. A passage from a nonfiction book (Carnes, 1999) was read aloud in the lecture. Idea units representing main points, important details and unimportant details were selected beforehand (Rawsome & Kintsch, 2005). Participants were instructed to take either organized or transcribing notes. In the organize condition, they were told to paraphrase and take notes in their own words. In the transcribing condition, participants were asked to transcribe and record as much of the lecture as possible. After the lecture, the participants had 10 minutes to freely write down what they could recall from the lecture. Afterwards, they took a 10-minute short answer test about the details of the lecture. Regarding note content, more idea units were recorded in computer notes over longhand notes and in transcribing notes over organized notes. For the free recall test, computer note takers recalled more idea units than their longhand counterpart. Taking. 20.

(31) . computer notes also lead to a larger proportion of main idea units, while there was no effect of modalities on important and unimportant details recall. In general, the encoding function of note-taking was most beneficial to computer note takers under transcription instruction in this experiment. They resulted in not only more notes taken but also better memory recall. Another possible explanation may be that information recorded could be more easily retrieved compared to what was simply heard (Conway & Gathercole, 1990; Slamecka & Graf, 1978). While the transcribing group performed better in the first experiment with immediate recall, the deeper processing during taking organized notes may be more beneficial to long-term learning. The second experiment thus set out to discover the effect of taking transcription versus organized notes on immediate and delayed posttests. Participants were 76 undergraduate students. The materials were the same as those used in the first experiment. All the participants took notes with computers and were asked to either take transcription or organized notes. Half of them took the free recall test and short answer test immediately while half of them took the tests after 24 hours. Comparing the performance on free recall test, the organized-notes groups performed equally well on immediate and delayed test. Whereas for those who were instructed to try to transcribe the lecture, performance on delayed recall was significantly poorer than that on immediate recall. The finding on short answer test was similar, with participants who took organized notes performed significantly better on the delayed test than those who did transcription. In general, the pattern of performance in the second experiment replicate that in the first experiment on. 21.

(32) . immediate posttests. However, the results reversed on delayed posttests that the deeper processing of the lecture information while taking organized notes yielded superior performance after a 24-hour delay. Therefore, it could be suggested that taking organized notes lead to better long-term memory retention. The third experiment then explored the effect of studying notes on delayed posttest. Participants were 72 undergraduate students and the materials were the same. They were asked to take either transcription or organized notes on a computer. Half of them were given the opportunity to study their notes for five minutes after they completed the lecture, the reading span and lexical decision tasks. All of the participants returned after 24 hours and took the free recall and short answer posttests. As in the free recall test, opposite pattern was observed comparing to the second experiment when participants did not study their notes. When participants were given the opportunity to review their notes, the transcription group recalled significantly more idea units than the organized group. Considering the performance on short answer test, there was no significant effect of note-taking strategy or study on overall recall, but minor interaction. When participants were not given opportunity to study their notes, those who took organized notes performed better. On the contrary, when they were able to review their notes shortly after the lecture, those who transcribed performed better. Overall, the benefit of taking either organized or transcription notes were shown in immediate posttests in both pen-and-paper and computer conditions. However, students who took transcription notes with computers resulted in significantly better test performance. Transcription notes, in general, were more beneficial in immediate. 22.

(33) . posttests and delayed posttests with the opportunity to review. Whereas taking organized notes yielded better performance in long-term learning. Due to the fact that participants were explicitly instructed to take certain kind of notes in this research and that participants took notes with only computer in both Experiment 2 and 3, further research on natural note-taking habits would be needed to investigate the differences between taking longhand versus laptop notes.. 2.3.1.3 Kirkland (2016). In consideration of the conflicting results in Bui et al.’s (2013) research and Mueller and Oppenheimer’s (2014) study, Kirkland (2016) went further to investigate whether participants’ lecture comprehension and retention would be influenced by taking notes through their preferred modalities. Participants were 105 undergraduate English speakers. They listened to two lectures accompanied by PowerPoint slides. They were asked beforehand whether they preferred longhand or computer notes. During the lectures, half of the students in each group were allowed to take notes with the modality they preferred while the other half were asked to take notes with the modality they were not used to. The longhand group were provided with pen and paper while the computer group took notes on Microsoft Word with an Apple iMac. Afterwards, they were given five minutes to study their notes. They then completed distractors tasks for thirty minutes and finished two paper-based comprehension posttests, consisting of respectively specific and conceptual multiple choice-questions. They had to hand in the first test and receive the second test from the researcher. Finally, they completed a. 23.

(34) . questionnaire regarding their note-taking tendencies (of longhand, computer and no notes) and note-taking preferences. The tests were scored and the content of the notes were analyzed. In general, longhand note takers and computer note takers showed no difference in test performance. While the overall score of the specific test was superior than the score of conceptual, the two groups performed equally well on both tests. There was no significant interaction between note-taking modality and test type. Furthermore, the main effect of whether participants used their preferred modality was not significant. Only those using nonpreferred modality in the longhand group performed marginally worse than other groups. Considering note content, computer notes result in significantly more words recorded and more verbatim overlap between the notes and the lecture transcription. Preference of modality did not have an effect on note content. Regarding the questionnaire, participants reporting they took longhand notes had a higher tendency to take notes comparing to their computer counterparts. In general, preference of taking computer notes was positively linked to taking no notes, indicating that participants who preferred computer notes were more likely to not take notes during lecture. Previous studies have found that, regardless the modality, taking notes was beneficial to test performance in lecture condition (Bui et al., 2013; Kirkland, 2016; Mueller & Oppenheimer, 2014). However, conflicting results were found considering test timing (immediate or delayed posttest) and test types (factual or conceptual questions). A recent research then shifted the focus to text condition, setting out to. 24.

(35) . uncover the potential effectiveness of note-taking on reading comprehension (Howirtz, 2017).. 2.3.2 Empirical study of longhand vs laptop note-taking effects on reading comprehension. 2.3.2.1 Horwitz (2017). Following the pioneering research of Mueller and Oppenheimer (2014), Horwitz (2017) conducted an extended study probing into the impact of studying and creating (longhand and laptop) notes on text comprehension. Two experiments were carried out in the study. In the first experiment, note-taking modalities and note review chances were set as variables in relation with learners’ reading comprehension. 48 college students enrolling in the course of General Psychology participated in the experiment. They were randomly assigned into four groups: laptop note-takers, longhand note-takers, laptop note-receivers and longhand note-receivers. A passage from the first chapter of Fundamentals of Marketing (Kerin, Hartley, & Rudelius, 2015), an introductory textbook on marketing, was chosen as the reading material. Participants were asked to read the passage by heart as if they were studying for an exam. In addition, they were not allowed to reread the passage. All participants took a pretest to show their prior knowledge for marketing. They then read a printed passage and the note-taking groups took notes either on white printer paper or on a blank Microsoft Word document on a personal laptop. Afterwards, they took a distractor test, studied the self-created or received notes, completed another distractor test, and finally took the. 25.

(36) . comprehension posttest. Note-takers reviewed their own notes and note-receivers studied either longhand or laptop notes from their counterparts. Longhand notes were typed to prevent misunderstanding from illegible handwriting. The results showed that there was a general increase of test scores after reading, especially when the questions were factual. However, surprisingly, there was no significant interaction between note-taking modalities and overall test performance. Using Welch 2-sample t-tests to determine individual growth, the only difference found was that laptop note-receivers showed a marginally significant improvement over their longhand note counterparts. A second experiment was then carried out in order to explain these results that were inconsistent with Mueller and Oppenheimer’s (2014). In the second experiment, a no-note group was created to explore whether creating or studying notes affect reading test performance. They underwent a similar procedure as those in the first experiment, only they did not create nor study notes. Instead, they had a longer distractor test to fill up the time of note reviewing section. Therefore, they took a pretest, read the passage, completed two distractor tests and finally answered the posttest. The time spent in total was the same as the first experiment. The results of this no-note control group were then compared with four other groups. In general, all five experimental conditions showed similar pretest/posttest improvement. Only the participants who received laptop notes were found to improve more than other participants did. The results suggested that creating either longhand or laptop notes did not have a significant benefit to reading comprehension.. 26.

(37) . Participants may have mostly learned from the reading passage itself instead of their notes. For factual questions, longhand groups did not outperform laptop ones, perhaps because they did not have many materials to study. These findings replicate previous research on lecture note-taking (Lalchandani & Healy, 2016; Mueller & Oppenheimer, 2014) that both groups show similar performance on factual recall. On the contrary, the benefits of longhand notes have been reported to be significant on conceptual questions in previous studies (Lalchandani & Healy, 2016; Mueller & Oppenheimer, 2014). However, this was not shown in Horwitz’s (2017) study. Multiple reasons may account for these inconsistent test results. First, longhand learners’ may be too tired from taking generative notes that require deeper mental processing. Possible exhaustion and lack of motivation may lead to worse performance in the posttest. Second, fundamental differences between the acts of listening and reading may lead to various learning outcomes that are not comparable. As for note contents, significantly more words were found in laptop notes over longhand notes. There was also a higher percentage of overlap between learners’ laptop notes and the reading passage. The average overlap in this study was also higher than the findings in Mueller and Oppenheimer’s (2014) research, simply because it is easier to copy verbatim notes from reading passages than listening to lectures. However, the analysis of notes quality (word count and verbatim overlap) and test performance showed no significant correlations. There were other possible reasons for the absence of longhand note-taking benefits. In this study, note-takers were told that their notes would be given to the. 27.

(38) . note-receiver group in the reviewing section. This could have resulted in non-organic note-taking performance and prevented personal meaning-making process. Moreover, note takers may spend less time reviewing the notes seriously because they had just created the notes a short period of time before. They may have taken less effort in reviewing the notes and taking the posttest. Horwitz’s (2017) study is the first to investigate the effects of note-taking modalities on reading comprehension. Compared to lecture conditions, whether laptop text notes harm learning remains relatively unclear. The limitations of this study are threefold: its small sample size may have led to no significant differences in the result; the short time between reading and reviewing may have harmed the motivation of studying notes; and finally, some conceptual questions that did not require reading but common knowledge could have affected test accuracy.. 2.3.3 General findings from empirical studies of longhand vs laptop notetaking. In both lecture and reading conditions, studies of longhand versus laptop notetaking have typically included an analysis of note content and post-reading comprehension performance. While there is a greater consensus in the findings of note content, contradictory results have been found in test performance (see Table 2). Findings will be further elaborated in the following sections.. 28.

(39) . Table 2 Summary of the results of relative studies Study. Condition Test Delay. Factual Test. Conceptual. Word Count. Performance Test Performance. Muller &. Listening. Oppenheimer (Lecture). After 30. Equal. mins. (2014). Longhand. Laptop notes:. group. more words. performed. and more. better. verbatim overlap. Bui,. Listening. Immediate Laptop group: Larger. Laptop notes:. Myerson, &. (Lecture). recall. proportion of main idea. more notes. Hale. units recalled. taken. (2013). Laptop note takers, especially those who take transcription notes, has better memory recall Listening. 24hr. Participants were all. (Lecture). delayed. computer note-takers.. test. Taking computer organized notes performed better than transcription notes. Kirkland. Listening. After 30. (2016). (Lecture). mins. Equal. Equal. Laptop notes: more words and more verbatim overlap. Horwitz (2017). Reading. 20 min. equal. equal. Laptop notes:. (including. more words. 6 min of. and more. reviewing. verbatim. note). overlap 29.

(40) . 2.3.3.1 Analysis of note content. The quality of notes was usually analyzed based on word counts and verbatim overlap. When analyzing the content of different notes, laptop note-taking resulted in significantly more words than hand-written note-taking. This is because typing is usually faster and less laborious than handwriting. While one hand is used to write, up to ten fingers are used to type. In handwriting, a closed system is formed with a pen held in one’s hand (Garman, 1990). On the contrary, the articulators, with fingers typing on the keyboard, work in parallel when typewriting. For casual adult typists, the average typing speed is 41 words per minute (WPM), whereas handwriting speed is around 22 to 31 WPM (Fort, 2014). On top of that, there is a ceiling for handwriting speed because when WPM increases, legibility decreases (Mangen & Velay, 2010). In one of the pioneering studies targeting the potential differences between longhand and laptop note-taking, learners were assigned to either transcribe, i.e. record as much as possible, or take organized lecture notes, i.e., write in their own words (Bui et al., 2013). On average, notes taken by laptops contained more units of ideas originated from the lecture. Interestingly, in handwriting, explicit instruction of asking learners to write as much as possible did not result in larger proportion of idea units comparing to the organized notes group. One possible explanation may be the ceiling of handwriting WPM imposed by physical limitation (Mangen & Velay, 2010). Recent research in the free note-taking of lectures and reading passages evinced similar results, with participants using pen and paper writing fewer words than their laptop counterparts (Horwitz, 2017; Mueller & Oppenheimer, 2014).. 30.

(41) . Moreover, using three-word chunks as the measure, more overlaps between students’ notes and lecture transcript were found in the group of laptop users, which implied that using a laptop may result in more verbatim notes (Mueller & Oppenheimer, 2014). In a follow-up experiment, where learners were explicitly told not to take verbatim notes, the results replicate findings in the previous experiment (Mueller & Oppenheimer, 2014). By the same token, a study on text note-taking also showed more verbatim overlap between reading passages and typed notes (35.47%) comparing to longhand notes (19.98%) (Horwitz, 2017). The ability to type faster than one can write makes it possible to record more words in a limited timeframe but also implies more verbatim notes. While shallower mental processing is included in taking verbatim notes and may undermine encoding benefits, the influence on learning comprehension are still under debate.. 2.3.3.2 Comprehension test performance. Studies on test performances of note-taking focus mainly on input comprehension and factual recall (e.g., Bui et al., 2013; Horwitz, 2017; Kirkland, 2016; Mueller & Oppenheimer, 2014). As previously mentioned, multiple levels of representation (i.e., surface structure, text-based and situation model levels) affect comprehension and recall (Dijk & Kintsch, 1983). Different tasks were thus designed to assess learners’ understanding of input (Butler, 2010; Rohre, Taylor, & Sholar, 2010; Wolf, 1993). While many of them explored on lecture comprehension, others dealt with reading comprehension. Methods and results of both kinds of studies will be included below.. 31.

(42) . Comprehension is the ability to process audio or textual input, understand the words as they are presented and link back to learners’ prior knowledge (Vandergrift, 2007; William, 2009). As in Kintsch’s Construction-Integration (CI) Model of text comprehension (1988), scope of understanding is located along a local-to-global continuum. Thus, regarding the effects of note-taking, typical tasks of testing comprehension can roughly be divided into two types: local processing and global processing tasks (Mueller & Oppenheimer, 2014; Peper, & Mayer, 1986). Local processing tasks include verbatim recognition and factual recall of keywords and detailed ideas. Both recall and lower level comprehension are measured in these tasks. On the contrary, global processing tasks require higher level comprehension. The abilities to categorize and link different parts of the material, recognize the main concepts, summarize the text and make inferences are assessed in these tasks (Van Dijk & Kintsch, 1983). Typical local processing tests are identification and recall of detailed facts. For instance, in Bui et al.’s (2013) study, participants were tested on important and unimportant details with multiple-choice questions. Findings in the first experiment have shown that longhand group and computer group performed equally well in immediate posttest. However, in the delayed posttest in the second experiment, participants who took organized computer notes performed better. While longhand note taking was not explored in this experiment, longhand note takers were known to produce more notes in their own words (Bui et al., 2013). Therefore, it would be worth exploring the comparison of longhand versus laptop natural note taking habits. In studies with natural conditions where participants can freely take notes, learners. 32.

(43) . using different modalities did not show difference on factual lecture or reading comprehension in 30-minute delayed posttests (Horwitz, 2017; Kirkland, 2016; Mueller & Oppenheimer, 2014). On the contrary, the benefits of encoding have been proved to be more helpful when completing global processing tasks in the empirical study of Mueller and Oppenheimer (2014). In the posttest containing multiple-choice and short-answer questions, longhand participants outperformed their laptop counterpart on conceptual and application tasks. However, this superiority wasn’t significant in Kirkland’s (2016) study on lecture comprehension and Horwitz’s (2017) study on reading comprehension. There was no difference in the performance between two groups with different note-taking modalities. One reason may be that conceptual comprehension was tested in multiple-choice questions in these studies. Another may be that listening and reading are two different information processing systems and that their results could not be directly compared. The generalization of the results from previous studies are still debatable and further research is therefore needed.. 2.4 Major Findings and Research Gap Note-taking, with its encoding and external storage functions, is generally considered an aid to learning. Notably, taking generative, non-verbatim notes that require learners’ inferencing creates meaningful learning and suggests stronger encoding benefits. In reading comprehension, Van Dijk and Kintsch’s (1983) model depicts multiple levels of meaning construction during reading. Actively engaging in reading, e.g., note-taking, is said to encourage deeper understanding such as situation. 33.

(44) . model to take place. As technology has been gradually incorporated into educational settings, a new issue considering note-taking modalities has emerged. Input comprehension may be impacted because of the shift from handwriting to typing and the subsequent influence on cognitive processing. On the one hand, handwriting, with more kinesthetic engagement than typing, exclusively creates a sensory-memory trace that enhances learning and recall. On the other hand, the easiness of using a keyboard, the flexibility in terms of editing and the incomparable production speed still give typing the overall advantage over handwriting. Regarding the comparison between longhand and laptop note-taking, note content analysis has revealed more words and verbatim overlap in laptop notes. In order to evaluate learning outcome from note-taking, various comprehension task types ranging from local to global processing have been used. Longhand note-taking also leads to better results in global-conceptual questions on lecture comprehension. However, the findings in text comprehension did not show difference between two groups. Previous research directly addressing the issue of longhand versus laptop notetaking either focus on lecture comprehension or fall short of speaking to real-world settings (Bui et al., 2013; Kirkland, 2016; Mueller & Oppenheimer, 2014). Respecting a L2 graduate school context, no study to date has investigated the potential different influences of longhand versus laptop note-taking on research paper comprehension. The present research was designed in order to fill in this gap and perhaps provide insights for higher education teachers and learners.. 34.

(45) . CHAPTER 3 METHODOLOGY The present research sets out to uncover the potential differences between longhand note-taking and laptop-based note-taking. How these modalities of spontaneous text note-taking impact reading comprehension, including local and global understanding, is also investigated. Of the few previous studies on this topic that can be found, those that have been undertaken were mostly set in lecture conditions. Some were not natural in design, and participants were explicitly asked to take a certain type of notes (verbatim or organized) (Bui et al., 2013). Others assessments were limited to word-level recall (Lin & Bigenho, 2011). More recently, Mueller and Oppenheimer (2014) discovered the benefits of longhand over laptop note-taking in aiding conceptual understanding; however, again this experiment was carried out under lecture settings. Only one study to date has directly addressed this issue in reading comprehension (Horwitz, 2017). However, no significant correlations were found in note-taking modalities or text comprehension. One reason may be that participants were not taking natural notes. They had been told that other participants would read their notes, and may therefore have taken more general notes instead of personally meaningful notes. In addition, reading and listening are fundamentally different, leading to inconsistency in test performance. This research follows Mueller and Oppenheimer’s (2014) study by applying a similar procedure and comprehension test. The current experiment also takes Horwitz’s (2017) study into consideration by applying a similar reading. 35.

(46) . comprehension test. The goal of this research design is to form a better understanding of the impact of note-taking modalities on research paper comprehension. The research methodology will be described in the following five sections: Section 3.1 begins by providing information about the participants; Section 3.2 describes the materials while Section 3.3 illustrates the instruments used in this study; Section 3.4 then outlines the procedure of data collection; Section 3.5 will provide insight into methods of data analysis; and finally, Section 3.6 summarizes the chapter and contains the author’s hypothesis.. 3.1 Participants The participants of the present study consisted of 30 graduate students from National Taiwan Normal University. Four participants were excluded; two because of not having taken any notes, and two because of not following the instructions. The majority majored in Teaching English to Speakers of Other Languages (TESOL) while others majored in linguistics; both MA programs were offered by the Department of English. They were all foreign language learners of English. In order to apply for the TESOL graduate program, students had to reach at least B2 (Vantage) level of the Common European Framework of Reference for Languages (CEF). Score concordance comprised passing the high-intermediate level of General English Proficiency Test (GEPT), getting more than 92 on the TOEFL iBT test or reaching 6.5 on the IELTS test. Participants from the Linguistics program in the present research have also reached the B2 level by passing these tests or receiving certain certifications. During the training of their graduate study, English passages from. 36.

(47) . research papers or textbooks were selected as classroom materials. All lectures were also delivered in English. Moreover, in most courses, students were asked to deliver a presentation based on assigned or self-selected research papers. Before graduation, they were also required to either present their papers at an academic conference or pass a subject examination. To prepare for exams, students needed memorize passages and have a deep understanding of related research papers. In short, the participants were all similar in terms of English proficiency and were all familiar to reading English research papers. During the present reading experiment, participants were randomly assigned to the longhand note condition or the laptop note condition, in which they used different modalities to take notes from the reading passage. Participants were between 22 to 30 years old in both groups.. 3.2 Material and Design 3.2.1 Reading Source Research papers were chosen as the target material for two reasons. First, participants in the present study were not only familiar with but were also motivated to read the research papers because, as previously mentioned, the research papers were closely related to graduate students’ study routine. Second, reading research papers may be more challenging and may highlight the functions of note taking. Learners have been found to undergo deeper mental processing when dealing with more difficult tasks (Oded & Walters, 2001). Since research papers are more complicated in nature and contain higher density of knowledge than common reading. 37.

(48) . materials, being actively involved in reading (i.e. taking generative notes in this case) may bring exceptionally positive outcomes.. Table 3 Information of the Reading Material Title of the. Parents and children in supermarkets: Incidence and influence. Research Paper Authors. Bill Page, Anne Sharp, Larry Lockshin, Herb Sorensen (2018). Total Words. 6393 words. Abstract. This research looks at the primary householder purchase context of grocery shopping and establishes the incidence of children accompanying adult shoppers. It identifies the effect of their presence on the spend, time taken to complete the trip and the route taken in-store. Observations are analyzed using exit interviews and structured observation of the in-store location of shoppers across two Australian states and four grocery retail outlets. Refuting the commonly held assertion that taking children shopping makes people spend more, accompanied shoppers do not spend more than unaccompanied shoppers, but rather shop 15% faster, tending to avoid busy areas in-store. This has implications for store layout and services offered. Products for children and parents need to be placed in areas where parents are more comfortable (that is, less busy areas), but also merchandised in ways that make it easy for parents to shop at their faster pace. The balance of these two needs is a direction for future research.. Following previous studies (Mueller & Oppenheimer, 2014; Slotte and Lonka, 1999), the criterion for choosing the reading materials was that the content be interesting but unfamiliar to as many participants as possible in order to prevent 38.