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Information For Educators

 
  1. Problem description
  2. How can Roads to Academic Reading help?
    Virtual tour of site
  3. Tools on this site
    1. Summary of tools
    2. Research basis for tools
    3. How can this research improve teaching?
    4. What does text-profiling look like?
    5. Step-by-step instructions for using Text Profiler
  4. How can text-profiling help ESL/EFL/EAP teachers?
  5. How can text-profiling help faculty who teach academic disciplines?
  6. Text-profiling for students
    1. Identifying "high-priority" AWL words
    2. Selecting and storing unfamiliar words and phrases in Word Bank
    3. Translations for AWL words and their derivatives
    4. Automatic generation of customized glosses
    5. Features of glosses generated by Text Profiler
    6. What the research says about glosses
  7. Vocabulary Flashcards
  8. Vocabulary Exercises
  9. How is this site different from other vocabulary sites?
    1. Exercises that teach, rather than test
    2. Words as "lenses"
    3. Automatic self-test option
    4. Selection of AWL words: breadth vs. depth
  10. Who else can benefit from Roads to Academic Reading?
  11. Suggestions for classroom activities
    1. Ideas for classroom use
    2. Tips for teaching students to use Text Profiler
  12. Your contributions
  13. Future directions
  14. Bibliography

Information for Educators

  1. Problem description

    Many non-native English speakers leave high school without learning the academic terms and concepts they need in order to cope with academic texts in English at college or university level. Many of these words, such as "evidence", "context" and "bias" are much more than labels: they are powerful concepts that help readers critically evaluate text content.

    Students who enter college or university without an adequate English vocabulary:

    • constantly interrupt their reading to look up unfamiliar words.
    • have fewer cognitive resources available for in-depth processing of text content and implementation of higher-order thinking skills.

    Helping these students become effective readers of academic texts is one of the biggest challenges facing teachers of English for Academic Purposes (EAP). However, allocating adequate classroom time to helping students acquire the rich network of academic terms that form the basis of academic literacy is often an almost impossible task due to the following classroom-related constraints:

    • "Zero-sum" nature of classroom teaching

      Allocation of limited teaching time to vocabulary instruction leaves less time for teaching reading comprehension strategies, and essential features of academic texts such as rhetorical organization patterns.

    • Heterogeneous classes

      Constraints related to students' timetables and teachers' schedules often result in students from different disciplines studying the same EAP course, despite their different needs and diverse levels of prior knowledge.

  2. How can Roads to Academic Reading help?

    This site provides a freely available set of open educational resources (OERs) that form an integrated learning environment to help users learn and remember high-frequency general academic words on Coxhead's (2000) Academic Word List (AWL).

    These instructional tools can be used either for independent study or as supplementary teaching materials. For more on how these tools can be used to supplement classroom teaching, go to suggestions for classroom activities.

    The tools on this site can help you become a faster, more effective reader of academic texts in English. These tools include:

    • Text Profiler
    • Flashcards
    • Exercises
    • Additional resources such as reading comprehension strategies, explanations of discourse markers, linguistic structures and organization patterns that characterize academic texts in English.

    Click here for a virtual tour of tools on this site.

  3. Tools on this site
    1. Click here for a summary of tools on this site.
    2. Research basis for tools

      Leading researchers in the field of SLVA (second language vocabulary acquisition) and CALL (computer-assisted language learning) have conducted large-scale computerized analyses of hundreds of academic texts. Their results show that a relatively small number of English words frequently appear in academic texts, and that these words can be divided into 3 groups:

      • Group One: Words that appear on lists of 2000 commonly used words in English.

        Two well-known lists of words in this category are West's (1953) General Service List (GSL) (http://jbauman.com/aboutgsl.html) and Nation's recently developed 1-2000 lists based on the British National Corpus (http://www.lextutor.ca/vp/bnc/nation_14). These words make up between75% to 80% of words in any academic text. The remaining 20 -25% of words in academic texts consist of words in Group Two and Group Three.

      • Group Two: Words that appear on Coxhead's Academic Word List (AWL)

        The 570 general academic words on this list were selected on the basis of both frequency and range. This means that words on this list appear more frequently than other words across many academic disciplines. For more on the AWL, see Coxhead's website.

        It is important to note that Coxhead excluded from the AWL all words which appeared on West's GSL. The GSL list was compiled during the 1940's and includes words which were then considered of greatest "general service" to learners of English. Consequently, Coxhead describes the AWL as "a list that does not include words that are in the most frequent 2000 words of English".

        According to Hyland and Tse (2007), the AWL may not be as general as it was intended to be. This observation is supported by the relatively large number of AWL words that also appear on Nation's 1-2000 BNC-based lists (Barth and Klein-Wohl, 2011).

        However, in contrast to Hyland and Tse, we believe that AWL words that "overlap" and also appear on Nation's BNC 1 -2000 list form a fourth group of words that can contribute towards prioritizing instruction of high-frequency general academic terms.

        The majority of these overlapping words appear on the first 5 AWL sublists which indicates that they appear far more frequently in academic texts than words on the last 5 AWL sublists. Consequently, these words represent an excellent starting point for high school teachers who want to "teach for tomorrow" and prepare their students for college or university.

        For detailed information on relative frequencies of sublists, see Nation (2001), p. 190.

      • Group Three: Words not included in the Groups One and Two.

        These off-list words usually include "technical", discipline-related and subject-specific words, infrequently used English words, names of people and places, etc.

    3. How can this research improve teaching?

      The groups of words identified by computerized analysis of academic texts form the research basis of Roads to Academic Reading's Text Profiler. This tool enables users to copy-paste their digital texts into a textbox that sorts the words in users' texts into the groups described above.

      The Text Profiler highlights AWL words in the users' texts to indicate which words they should focus on first, instead of trying to remember all the words in their texts.

      Focusing on words that constantly appear in academic texts can:

      • make the task of learning vocabulary more manageable.
      • gives students the most benefits in return for the time and effort they spend on learning English vocabulary.

      One of the central goals of this site is to extend the use of text-profiling to additional populations who may not yet be aware of the potential benefits of text-profiling for both teachers and students.

      For over a decade, Heatley, Nation and Laufer's (1994) Range program, as well as Cobb's VocabProfiler have provided free access to text-profilers. However, it is still not clear to what extent teachers, instructional designers and materials developers use these sites regularly to support curriculum decisions and prepare instructional materials.

      Although text-profiling has many advantages for both teachers and students, our initial research indicates that these tools are not yet utilized extensively in either pre-service teacher education or in workshops for in-service teachers. This reinforces Schmitt's (2008) observation that although there is substantial research available on vocabulary learning, much of this research has been slow to filter down into mainstream pedagogy.

    4. What does text-profiling look like?

      Step 1

      Users copy-paste their own academic texts into the text-profiler.

      text profiler

      Step 2

      Users see words in their own texts sorted and color-coded into 4 types of words.

      text profiler

      Step 3

      Users select and store unfamiliar words or phrases in their Word Bank.

      text profiler

      Step 4

      Words and phrases sent to Word Bank form part of an automatically-generated gloss or customized translation table.

      text profiler

    5. Click here for step-by-step instructions for using Text Profiler.

  4. How can text-profiling help ESL/EFL/EAP teachers?

    Faculty who teach English can use Roads to Academic Reading's Text Profiler to identify which words in a digital text are high-frequency general academic words that constantly appear in academic texts.

    Highlighting general academic words in texts represents a "teaching for tomorrow" approach that focuses on high-frequency words which students will meet many times during their academic studies. This approach contrasts sharply with teaching difficult but infrequent words in specific texts. Instead of spending time on low-frequency words, these words and expressions can be added to the Text Profiler's Word Bank for glossing, in order to reduce dictionary lookups that interrupt the reading process.

    Text-profiling can help teachers to:

    • determine suitability of texts for specific groups of learners.
    • identify how selected texts should be adapted to meet the needs of specific classes.
    • assign flashcards and exercises as supplementary study materials before or during a lesson.
    • spend less classroom time on transmitting information and allocate more time to constructivist activities that help students move from receptive to productive knowledge of vocabulary.
    • generate automatic customized glosses or "translation tables" for their students.

    The importance of a multi-dimensional approach

    Although text-profiling can help educators make data-based decisions related to selecting and sequencing of texts, it is important to note that text-profiling is only one of the tools that can be used to make more effective decisions. For a review of these tools, see Hancioglu and Eldridge (2007).

    Similarly, the percentage of high-frequency academic words contained in a specific text can help teachers make data-based decisions regarding text selections. However, this is only one of many issues that should be factored into the equation when selecting learning materials and making curriculum decisions.

  5. How can text-profiling help faculty who teach academic disciplines to non-native English speakers?

    Faculty who teach academic disciplines and assign required reading in English to non-native English speaking students can use Text Profiler instead of simply expecting non-native English speakers to "sink or swim".

    Text Profiler can help faculty to:

    • assess the level of English required before assigning compulsory reading texts.
    • provide subject-specific glosses for a representative sample of compulsory reading texts to support text comprehension.

  6. Text-profiling for students

    Text-profilers currently available on teacher-support sites such as http://www.lextutor.ca/vp/eng include a great deal of information related to word types and frequencies. Although this information is extremely valuable to researchers and practitioners, our experience with teaching students to work with text-profilers indicates that many students do not perceive these data as directly relevant to their needs.

    Roads to Academic Reading's Text Profiler has therefore been designed as a user-friendly student-oriented tool which incorporates a number of features from our EAP students' "wish lists".

    These features include:

    1. Identifying "high-priority" AWL words
      • Needs-based criterion for selecting target words

        For students who are not native speakers of English, trying to learning all 570 words on the AWL may seem like a never-ending task. This site is designed to make this task more manageable by enabling students to identify which AWL words in their own texts they should focus on first.

      • "Overlaps" as criterion for selecting target words

        The text-profiler on this site has been pre-loaded with Prof. Nation's BNC-based lists of the 2000 most commonly used in English, instead of with West's (1953) General Service List. This feature enables users to see which words in their texts are "high-priority" words that appear on both Nation's 1 – 2000 word list as well as on Coxhead's (2000) AWL.

    2. Select and store unfamiliar words and phrases in Word Bank

      This feature enables users to:

      • automatically send all AWL words in their own texts in their personal Word Bank.
      • manually select and store in their Word Bank any unfamiliar single words as well as phrases, lexical bundles and expressions from any of the groups of words described above.

      Words sent to Word Bank are automatically converted into an easy-to-use customized gloss or "translation table".

    3. Translations for AWL words and their derivatives

      Text Profiler automatically provides possible translations for all AWL words and their derivatives which users select and send to their Word Bank.

    4. Automatic generation of customized glosses

      Words stored in Word Bank are automatically converted into a "translation table" that can be copied to clipboard for pasting into readers' files. Users can then use a word-processor to copy-paste and capture dictionary lookups for non-AWL words.

    5. Features of glosses generated by Text Profiler

      Glosses generated by our Text Profiler contain: text profiler

      • possible translations for AWL words and their derivatives.
      • sentences from users’ text with target word in context.
      • space for users to add references, explanations of subject-specific terms and personal notes.
      • hyperlinks to flashcards and exercises for 300 AWL words for pre-reading and/or post-reading activities to support systematic learning of target words.
      • Possible translations for AWL words and their derivatives

        Because meaning is context-dependent, users are given a choice of possible translations for AWL words that appear in their texts. Users select translation options which are most appropriate for their specific context. Automatic translations are currently available only in Arabic and Hebrew.

        Until additional translations are available for pre-loading into our Text Profiler, users who are not Arabic and Hebrew speakers will have to complete translation tables manually. We are currently looking for partners to help us add translations of AWL words into additional languages.

      • Sentences presenting target word in context

        Glosses or "translation tables" contain automatically-generated extracts of sentences from the user’s text to show how target words are used in context. These extracts help users check that the translation they selected "makes sense" within the context of their specific text. In addition, "anchoring" the target word can contribute significantly to memory retention and retrieval.

    6. What the research says about glosses

      The two main purposes of glosses are (a) to give readers information about unknown words in the text with minimal interruption to reading and (b) to help readers pay attention to words in the text that are important to understand and remember.

      A number of researchers such as Hulstijn, Hollander and Greidanus (1996), Chun and Plass (1996), Nation (2001) and Yoshii (2006) indicate that use of glosses correlates with improved rates of vocabulary learning. According to Watanabe (1997), these correlations may partially be explained by the increased number of exposures to target words and increased processing related to use of glosses.

      As Watanabe points out, glosses with multiple choice translations, which require readers to select a translation from possible alternatives, give readers three meetings with a target word: (1) noticing it in a text, (2) seeing it in the gloss and (3) looking back at the target word in the text to see which translation in the gloss fits the reader’s specific context.

      Although glosses can increase vocabulary learning from incidental exposure to target words, the process of manually preparing multiple-choice or even single L1 – L2 glosses "from scratch" can be very labor-intensive for teachers. One of the central features of Text Profiler is the automatic conversion of words selected by readers for storage in Word Bank into user-friendly glosses or "translation tables". These glosses can be used for pre-reading preparation, or for reference while reading to reduce the number of dictionary lookups that interrupt the reading process.

  7. Vocabulary Flashcards

    Noticing AWL words in authentic texts is an important road to efficient academic reading. However, incidental exposures to target words are only one of the steps required to ensure retention of newly-learned words.

    In order to reinforce incidental exposures to AWL words, AWL words that appear in the user’s glosses are hyperlinked to 300 vocabulary flashcards and sets of exercises. These tools support pre-reading preparation and/or post-reading activities to consolidate newly-acquired words.

    Flashcards may be regarded by some teachers as a return to outdated “drill and kill” methods of language teaching, and this may be true when flashcards are used on their own for learning de-contextualized vocabulary items. In contrast, flashcards on this site provide users with background information to supplement and reinforce incidental exposures to AWL words which readers encounter in their own authentic texts.

    flash card

    Flashcards provide:

    • pronunciations, including changes in stress patterns related to changes in grammatical functions of target word.
    • L1 – L2 word pairs (Arabic and Hebrew only – watch this site for additional languages).
    • explanations of meanings that are frequently used in academic texts.
    • example sentences that illustrate the target word.
    • parts of speech for each target word.
    • additional meanings of target word when used in everyday contexts.

    Each flashcard is linked to a set of 6 vocabulary exercises.

  8. Vocabulary Exercises

    Description of exercises

    • Exercises include a range of different item types such as multiple-choice questions, sentence completion, matching and sorting exercises.
    • Each set of exercises consists of a graduated hierarchy of 3 basic level and 3 advanced level interactive exercises.
    • The 3 basic or beginner's level exercises establish the form-meaning connection by using synonyms, contextualization of target word, exemplification and elaborative processing of new information.
    • At the advanced level, exercises are designed to enhance knowledge of language in use by focusing on word parts and collocations. When applicable, the sixth and last exercise in the set goes beyond the word level and utilizes the target concept to teach academic conventions and reinforce critical thinking skills.
    • All AWL words used in the exercises in addition to the target AWL word are underlined for users who select a language option. Standing on the underlined AWL words with the mouse enables users to see possible translations.

    exercise picture
  9. How is this site different from other vocabulary sites?
    1. Exercises that teach, rather than test
      • Instead of simply testing to see what users know, exercises on this site feature 'teaching boxes'. These boxes give students specific background information that experienced teachers would usually provide during a lesson.
      • Beginner's level multiple-choice exercises require learners to identify 3 correct answers out of 4 answer options. Each correct answer provides additional information about the target word to reinforce the form-meaning link.
      • Corrective feedback helps users who are studying independently to understand and learn from their mistakes.
    2. Words as "lenses"

      Many AWL words such as "bias" and "evidence" represent powerful concepts which act as lenses that help students see when and how writers are trying to impose their opinions on the reader. These words lay the foundation for academic literacy and equip students with concepts that are crucial for exercising independent judgment and becoming a critical reader of academic texts.

      Words in this category have "mini-lessons" as the sixth and last exercise in the set. These exercises include generalizable teaching points related to academic conventions or metacognitive questions which effective readers ask themselves in order to implement critical and creative thinking skills. A magnifying glass icon differentiates these "mini-lessons" from standard reading comprehension exercises.

      exercise picture

      For additional examples, go to:

    3. Automatic self-test option

      After users have looked at flashcards and/or exercises for 5 target words, the program automatically generates a self-test option to ensure adequate "recycling" and reinforcement of newly-acquired vocabulary. The program analyzes users' test scores and recommends possible options for improving results.

      test picture
    4. Selection of AWL words: Breadth vs. depth

      In contrast to sites that provide one or two exercises for each AWL word, this site currently provides flashcards and a set of six exercises for each of 300 AWL words. These 300 words were selected by inter-rater agreement among a group of experienced teachers and materials developers who have been part of The Open University's English department for many years.

      These raters selected 195 words from the first 5 AWL sublists, and 105 words from last 5 sublists. An analysis of selected words on the last 5 sublists shows that these sublists include a number of key concepts, for example "bias" (sublist 8), that are crucial for the development of academic literacy and higher-order skills. These inter-rater results indicate that curriculum decisions to focus only on the first 5 sublists would exclude some concepts that are essential for helping students become more critical readers of academic texts.

      Reasons given by raters for not including words at this stage of the project include:

      1. Words which were judged to be useful in a relatively limited number of disciplines, for example "legislate" and "export".
      2. Words that do not warrant a set of 6 exercises in order to learn the target word. These words include:
        • words that can easily be explained by a symbol such as "positive" (+) or "percentage (%).
        • words which refer to concrete objects and can be easily be explained by a picture, such as "computer".
        • words that are loanwords in a number of languages and may already be familiar, for example "normal".

      Teachers who require exercises for these words can refer to a number of very useful sites:

  10. Who else can benefit from Roads to Academic Reading?

    Additional populations who can benefit from this website include:

    • EFL materials developers.
    • teachers who help students prepare for psychometric or English placement exams.
    • teachers of Academic Literacy programs.
    • instructional designers of Early College programs that prepare high school students for college or university.
    • curriculum planners who design enrichment programs for gifted students.
    • parents who home-school their children.

    Users of open educational resources (OER)

    • Although attempts are being made to translate some OER such as MIT's open courses into additional languages, the majority of OER are currently in English.
    • Tools on this site can give non-native English speakers the additional language support they need in order to maximize the potential benefits of open content.

  11. Suggestions for classroom activities.

    We recommend that before progressing to higher sublists, teachers ensure that their students know the “overlapping” words that appear on both Nation’s list of 2000 most common words in English as well as on Coxhead’s AWL. Most of these overlaps appear on the first five AWL sublists.

    1. Ideas for classroom use

      Teaching Objectives Suggestions for Activities
      Heterogeneous Classes:
      Dealing with different ability levels in the classroom.
      Students can work in class on different words according to their specific levels and needs.
      • Lower level students can work on words from sublists 1 – 3 and start with the exercises at the basic level.
      • Advanced students can work on words from higher level sublists and should continue to the advanced level exercises.
      Collaborative Work Students can work together in pairs or small groups in order to negotiate meaning and complete the exercises.
      Pre-Reading:
      Focusing on key vocabulary before reading a text.
      For teacher:
      • Use the Text Profiler in order to get a list of the AWL words in a specific text the students should know in order to understand the text.
      For students:
      • Lists of key words can be given to students to learn through use of the flashcards and vocabulary exercises before reading the text.
      Post-Reading:
      Reinforcing newly acquired vocabulary and learning additional meanings.
      • After reading a text, students can work on exercises in order to internalize and reinforce key AWL words that appeared in the text.
      • In cases where words have multiple meanings, these additional meanings can be taught and reinforced.
      Vocabulary Enrichment :
      Structuring "learning by doing" integrative tasks or webquests based on clusters of words to develop critical thinking.
      • In order to expand understanding of words, teachers can create clusters of words and related concepts. For example, a cluster of AWL words that are related to the target word "research" could include: variables, random, intervention, data, empiric, evidence, evaluate, reliability, validity, hypothesis, theory, predict, demonstrate.
      • Teachers can build integrative "learning by doing" tasks. around specific clusters of words. For example, a cluster of target words such as "criteria, evaluate, bias, evidence, neutral, authority and perspective" could be used as the basis for webquests that teach students how to evaluate information on the Internet.
      Independent Study: Students working alone in class or at home. Since students have free access to these Internet based tools, they can use them anywhere, anytime in order to develop their vocabulary knowledge.
    2. Tips for teaching students to use Text Profiler

    1. Teachers should emphasize that Coxhead put words on the AWL only if they frequently appear in a wide range of academic disciplines. Unless this basic concept is clear, students will not understand why words which they consider "academic" do not appear on the AWL.
    2. When selecting words for storing in Word Bank, students should check to see that they have selected all the letters of the word.
    3. Click here for step-by-step instructions on how to use Text Profiler.

  12. Your contributions

    This site is a work-in-progress and we would very much appreciate your suggestions. Please contact us and send us your feedback so that we can improve this site.

  13. Future directions

    The modular design of this site's infrastructure allows us to add the following components to Roads to Academic Reading's Text Profiler:

    • translation components in additional languages.
    • "banks" of translations for subject-specific discipline-related vocabulary.

    If you are interested in working with us to develop these directions, please contact us.

  14. Bibliography
    • Barth, I. & Klein-Wohl, E. (2011). Teaching students to use text-profilers: A needs-based approach to tertiary level English vocabulary instruction. International Journal of Computer-Assisted Language Learning and Teaching, 1(3), 86-98.
    • Chun, D.M. & Plass, J.L. (1996). Effects of multimedia annotations on vocabulary acquisition. Modern Language Journal, 80, 183-198.
    • Coxhead, A. (2000). A New Academic Word List. TESOL Quarterly, 34 (2), 213-238.
    • Hancioglu, N. & Eldridge, J. Texts and frequency lists: Some implications for practicing teachers. ELT Journal, 61 (4), 330 – 340.
    • Heatley, A., Nation, P. and Laufer, B. (1994). Range. Victoria University of Wellington, NZ. [available at http://www.vuw.ac.nz/lals.]
    • Hulstijn, J. H., Hollander, M. & Greidanus, T. (1996). Incidental vocabulary learning by advanced foreign language students: The influence of marginal glosses, dictionary use and reoccurrence of unknown words. Modern Language Journal, 80, 327-339.
    • Hyland, K. & Tse, P. (2007). Is there an "Academic Vocabulary"? TESOL Quarterly, 41 (2), 235-253.
    • Nation, I.S.P. (2001). Learning vocabulary in another language. Cambridge University Press.
    • Schmitt, N. (2008). Instructed second language vocabulary learning. Language Teaching Research 12 ( 3), 329-363.
    • Watanabe, Y. (1997). Input, intake and retention: effects of increased processing on incidental learning of foreign vocabulary. Studies in Second Language Acquisition, 19, 287-307.
    • West, M. (1953) A General Service List of English Words. London: Longman, Green and Co.
    • Yoshii, M. (2006). L1 and L2 glosses: their effects on incidental vocabulary learning. Language Learning and Technology, 10, 85-101.
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