assignment

need 1 page for task 1 and 1 page for task 2. task is in file “Task” attached
100plagarism
ATTACHED FILE(S)
Spring 2020 EDD771
Task 1 ::::::::::::::::::::
Article Review & Reflection 1

Instructions:
Please read the New York Times article: ‘Access to Literacy’ Is Not a Constitutional Right, Judge in Detroit Rules and answer the questions below using the following format: numbered responses
corresponding with questions, full sentences,1-2 pages, double spaced, please label and identify your work…
“NYT_2018” is the article attached
1) What is your answer to the first question of the article? Do students at poorly performing schools have a constitutional right to a better education?
2) Is this issue addressed in your school or work? If so, how?
3) How can data play a role in strengthening this cause?
—————————————————————————————————————————————————————————————————————————————————————————————-
Task 2 :::::::::::::::::::::::::::::
Article Review & Reflection 2

Instructions:
Read this article addressing quantitative research in literacy practice and respond to the following questions:
Article is “Honan_Small Data” attached. Need 1 page

1) Name two examples of how this article may (or may not be) relevant to your current practice).
2) Describe a scenario in your work where a measure of central tendency is/can be used. Which measure is used? How do you use it?
3) Describe a scenario in your work where a measure of variability is/can be used. Which measure is used? How do you use it?

57
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
Small data: Working with
qualitative information in the
literacy classroom
Eileen Honan | The University of Queensland, Queensland
A B S T R A C T
This paper describes the current emphasis on collecting and using quantitative data that encourages
the ‘quantification of everything’ (Mayer-Schönberger & Cukier, 2013, p.78). The author argues
that qualitative data provides more complex and nuanced understandings of how young people
engage with literacy teaching and learning opportunities in classrooms. Some useful examples of
methods that teachers can use to collect and analyse qualitative data in their literacy classrooms
are provided.
Introduction
There has been a rapid growth in interest and enthusiasm for ‘big data’ in educational contexts, both
internationally and in Australia. Use of large scale sets of data to inform the planning of literacy policies
and programs is underway in the USA and this has implications for literacy teachers in Australian
schools. As well, there is an increasing responsibility for literacy classroom teachers to collect and
interpret quantitative data, ranging from the regular administration of reading comprehension
assessment tests, to the interpretation of class and student NAPLAN (National Assessment Program–
Literacy and Numeracy) results. These two emphases have tended to push into the background the
vital importance of qualitative data that provide more in-depth and individualised understandings of
how young people engage with literacy teaching and learning opportunities in classrooms.
In this paper I provide an overview of the use of ‘big data’ in the USA to shed light on the
possible future uses in Australian contexts. I will then describe some of the current approaches to
the use of quantitative data in classroom contexts and provide a critique of the overemphasis on the
‘quantification of everything’ (Mayer-Schönberger & Cukier, 2013, p.78). I will argue that qualitative
data provides more complex and nuanced understandings of how young people engage with literacy
teaching and learning opportunities in classrooms. I will provide some useful examples of methods
that teachers can use to collect and analyse qualitative data in their literacy classrooms.
Overview of the use of ‘big data’ in the USA
The use of ‘big data’ has been growing exponentially globally as more and more personal information
is stored in databases. The term was first used in science contexts and has many different definitions. It
has come to mean the use of large sets of data that can be analysed to produce or ‘apply math to huge
quantities of data to infer probabilities’ (Mayer-Schönberger & Cukier, 2013, p.12).
In educational contexts, especially in the USA, there is a growth in attention to the possibilities
provided through collections of these large data sets about students. These collections are made
possible by the growth of cloud storage spaces used by education departments and systems. Data
collected at the student, classroom and school level are sent to the state or federal level department or
organisation, and these data can then be analysed to tailor online learning programs, track achievement
and attendance levels, or as one enthusiast suggests, ‘using a data-driven approach can help us teach
58
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
more effectively. At the same time, technology that leverages data can help students with day-to-day
learning and staying in school’ (Feinleib, 2014, p.174).
In the USA, examples of data collection methods include the use of mobile applications that
can collect information down to individual keystrokes. Teach to One is one company that uses data
collected through software to develop personalised quizzes and lessons. It claims that ‘Teach to One
students are assessed daily to determine current skill levels, and an algorithm employs these test results
to target content delivery for the following day’ (Ready, 2014). Renaissance Learning (2015) boasts
that their ‘database houses reading records for more than 10,700,000 U.S. students at more than
36,000 schools’.
These and other companies are using the term ‘learning analytics’ to explain their applications of
‘big data’ concepts to educational contexts. A research paper from the University of Bristol explains
the concept:
‘Learning analytics’ has been defined as: The measurement, collection, analysis and reporting of data
about learners and their contexts, for purposes of understanding and optimising learning and the
environments in which it occurs. Learning analytics interrogates learner-based data interaction (using
techniques such as predictive modelling, user profiling, adaptive learning, and social network analysis)
to inform or prompt actions or decisions based on the results. (Broadfoot, Timmis, Payton, Oldfield &
Sutherland, 2012, p.2)
Some of the inherent problems associated with privacy legislation and data security have already
been raised in the USA where ‘education-data companies are hiring chief privacy officers, testifying
before state legislatures and reshaping their messages to emphasise their data security. States rein in
access to student data or allow parents to opt out of data collection’ (Fleisher, 2014). One of the more
controversial initiatives was inBloom Inc., a company that wanted to link education-tech companies
with school districts ‘serving as a type of middleman for student data. Its system gives schools the
option of uploading hundreds of characteristics about students, including disabilities such as autism
or vision problems’ (Fleisher, 2014).
The implications for classroom teaching if these approaches are introduced into Australian schools
are many. Increasingly, the teacher’s role in identifying and diagnosing learning problems would be
removed, and even in the case of programs such as those promoted by Teach to One, the role of
teaching students how to overcome these problems would be taken by the software delivered on either
a computer or tablet or even smartphone. The focus for responsibility for assessing and teaching would
shift outside of the classroom, away from the generalist classroom teacher. Indeed, this shift is already
apparent in the collection of quantitative data in Australian classrooms that is then used in state and
federal government reports.
Current approaches to the use of quantitative data in classroom contexts
While the use of large sets of data is not yet as common in Australian schools as it is in the USA,
there has been a rapid increase in the amount of quantitative data collected in classrooms over the
last 15 years. The introduction of NAPLAN and the development of the MySchool website by the
federal government have necessarily required a greater focus on the collection of data at the school and
classroom level. As well, each state in Australia has its own systems and methods of data collection in
education– for example in, Queensland the Queensland School Opinion Survey is:
a suite of surveys on opinions on the school, student learning and student well-being from a parent/
caregiver in all families and a sample of students from each state school. Opinions on the school as a
workplace are sought from all state school staff and principals. Additional questions are included for
teaching staff on their confidence to teach and improve student outcomes, while principals are also asked
on their confidence to lead the school, including improvements in student outcomes. (Department of
Education, Training and Employment, Queensland, 2005–2015)
59
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
Classroom teachers are asked to distribute these surveys and participate in discussions about the
results, as well as administer and interpret the results of NAPLAN tests. Many schools have adopted
school-wide assessment tools such as:
• TORCH (Tests of Reading Comprehension; see Australian Council for Educational
Research (ACER), 2005–2010);
• CARS and STARS (Comprehensive Assessment of Reading Strategies, and Strategies To
Achieve Reading Success; see Hawker Brownlow Education, 2012);
• PAT-R (Progressive Achievement Tests in Reading; see ACER, 2012).
In many cases it is the classroom teachers’ responsibility to administer these tests, and then analyse
and interpret the data provided by the results.
Economists such as Pugh and Foster (2014) are especially interested in ‘third party’ access to
‘big data’ collected in Australia through the MySchool website. They cite the UK’s approach to their
National Pupil Database that includes ‘test and exam results, prior attainment and progression at
different key stages and data on gender, ethnicity, first language, eligibility for free school meals,
special educational needs, attendance and exclusions’ (p. 260). Pugh and Foster suggest there are
‘encouraging signals’ (p.262) that both federal and state level departments are increasing access for
academics and other researchers to ‘student-level’ data for Australia.
Quantification of everything
The first part of this paper has described a context where there is much enthusiasm and great promises
for the use of large sets of data to help improve teaching and learning. The message from governments,
private enterprises and researchers appears to be that these sets of quantitative data are the way of
the future. They claim that we will be able to track a student’s attendance, record and correlate that
with performance on standardised tests, while at the same time factoring in language background
and the schooling history of the parents. Teachers will be able to draw up records on each student to
show, for example, that on 27 May one student completed 8/10 spelling words correctly, while on 2
June the student only completed 5/10 correctly. The student will be directed to complete a series of
exercises in an online spelling program, where every day for 15 minutes the student sits in front of
a computer screen and identifies words spelt correctly or incorrectly from a range of multiple choice
items. The student is quiet; headphones play audio directions, even pronunciation assistance; whistles
and dancing bears perform in response to a correct guess.
Both these current emphases– the importance of ‘big data’ and the value of quantitative results–
shift our thinking about the possible measurements of student performance. Consider the difference
between using numbers to describe student performance (15/20 for a spelling test) and words
(frequent use of appropriate sentence structures for this text type). While both provide the reader
with information about student learning, the number appears to carry with it an assumption about
ranking. It is so commonplace today to use numbers in this way that it could be assumed that we
can quantify anything. Mayer-Schönberger and Cukier (2013) explain that ‘to datafy a phenomenon
is to put it in a quantified format so it can be tabulated and analysed’ (p.78). The quantification of
performance allows tabulation; tabulation allows ranking; rankings assume categories of best and
worst. Hierarchical thinking is taken for granted; students are assigned numbers to identify their level
of performance in relation to others (in their class, other classes, other states, even other nations).
For example, media releases from government ministers include statements such as: ‘Queensland now
ranks fourth in the proportion of students achieving the national standard on all strands in Years 3
and 5– with the exception of writing’ (Langbroek, 2014).
Media reports focusing on education’s perceived failures commonly use such rankings. For
example:
60
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
Australian teenagers’ reading and maths skills have fallen so far in a decade that nearly half lack basic
maths skills and a third are practically illiterate. The dumbing down of a generation of Australian
teenagers is exposed in the latest global report card on 15-year-olds’ academic performance. (news.com.
au, 2013)
It was many many years ago that Charles Dickens delighted his audience with a critical and satirical
view of the quantification of everything, personified in Thomas Gradgrind in Hard times (Dickens,
1961) who was a man ‘with a rule and a pair of scales, and the multiplication table always in his pocket,
sir, ready to weigh and measure any parcel of human nature, and tell you exactly what it comes to’
(p.12). In Chapter 2 of Hard times we are introduced to ‘Girl number twenty’:
‘Girl number twenty unable to define a horse!’ said Mr. Gradgrind, for the general behoof of all the little
pitchers. ‘Girl number twenty possessed of no facts, in reference to one of the commonest of animals!’
(pp.13–14)
It appears at times that Gradgrind would find the classrooms of the 21st century very familiar, as the
push to measure every ‘parcel of human nature’ becomes so easily accommodated into our schooling
systems.
Importantly, this rethinking about measurement and performance tends to push aside the
classroom teacher’s expertise, knowledge and understanding of qualitative data. Indeed, the impetus
for this paper was working with teachers who appeared to belittle this knowledge they had, who
brushed aside their existing understanding and skills with qualitative data in their eagerness to learn
how to interpret the graphs and tabulations provided in NAPLAN reports.
Importance of qualitative data
Qualitative data describes, but does not measure, observes what is there (often called naturalistic
observations), and can be useful to help us explain different aspects of occurrences. Here is an example
of the differences between a quantitative and qualitative analysis of data. In one project that I worked
on (van Krayenoord, Gillies, Honan, Moni, Western & Brereton, 2011), we designed and distributed
a survey to parents and the wider community surrounding participating schools. This survey was
designed to investigate community perceptions about the value of reading. Figure 1 shows a graph
that represents the responses given to one question in the survey that was related to the teaching of
reading.
There are some points about community attitudes to the teaching of reading that we can draw
from this graph.
• Nearly all items have high level of agreement;
• The message about parent involvement seems to have worked;
• Level of disagreement is strongest around the item about rich children finding it easier to
read;
• There is a strong agreement with the statement about individuals learning at different rates;
• There is a large number of ‘grey’ responses that neither agree nor disagree with the
statement about teaching using traditional methods– but then there are quite strong
opinions expressed about the teaching of grammar and the use of literature– which are the
specifics of a so called traditional approach.
Yet there are a number of unanswered questions about these responses. For example, there is
strong agreement with the statement about individuals learning at different rates. Does this reflect
understanding about the different theories about the teaching of reading, or are the respondents
sending a message to schools and teachers? (Don’t try to put everyone into the same box, or into the
same box of levelled readers).
61
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
There appears to be some sense that the respondents have embraced the messages that continually
appear on the front pages of our newspapers that ‘much more must be done’ which appears to
contradict the responses to other statements. And what are the reasons for the level of disagreement
being strongest around the item about rich children finding it easier to read? Because the community
thinks all kids should have the same opportunities? Because the community is reflecting the egalitarian
myth of ‘all Australians are equal’?
None of these questions can be answered through an analysis of the graph or of the data that lie
behind the graph. The only way of exploring the reasons for survey responses is to ask the respondents
further questions, through interviews or focus group discussions. These techniques for collecting data
are explored in the next section of this paper.
Collecting qualitative data
Most classroom teachers will collect both quantitative and qualitative data about their students’
learning and their own teaching practices. It is important to think about the problem or issue that is
being investigated first, and then make decisions about the type of data that would provide the most
useful information about that problem. Here are some examples of questions that teachers might be
interested in investigating and that would be best explored through collection of qualitative data.
Note the framing of these questions as open-ended and requiring exploration rather than a positive
or negative response only.
• Why do the boys in Grade 3 complain about reading lessons?
• How is reading comprehension taught in this class, school, district, state?
• How are digital texts used in literacy classrooms?
• Why is there a gendered difference in NAPLAN spelling results in Year 5 classrooms?
• How does an understanding of the reading process impact on student performance on
standardised reading comprehension tests?
While standardised tests and surveys can provide useful data about student learning, examining
Figure 1. Survey responses, from Honan, 2013
62
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
the reasons behind results and providing more nuanced accounts of the knowledge students have
about particular aspects of literacy are more likely to be completed using qualitative instruments. For
example, recording the interactions and behaviours of students with texts, as well as their knowledge
of how texts work, can be completed through observation and documentation techniques, such as
running records, anecdotal records, checklists, and portfolios. Many of these techniques are practised
by classroom teachers as part of their classroom assessment routines. However, systematic recording
and analysis of these data is sometimes ignored.
Collecting data about teachers’ pedagogical practices can be useful for a variety of purposes:
• demonstrating and modelling effective or new strategies;
• promotion or appraisal;
• demonstrating impact of professional learning on practice;
• reflecting on own pedagogy;
• identifying and answering research questions.
Tools that can be used to collect data about pedagogical practices include:
• classroom observation tools;
• interviews– pre and post observation;
• video and audio recordings;
• ethnographic observations– rich and thick, using templates;
• stimulated recall and reflection;
• reflective journals.
In some cases, classroom teachers find it useful to use an action research cycle to plan their use of
data tools. As noted in the example of an action research cycle provided below, data collection occurs
at various stages, from the first step of identifying the problem to looking at what happened and using
results to update and modify the plan.
Figure 2. Action research cycle (from Honan, Evans, Paraide, Reta & Muspratt, 2012)
Analysing qualitative data
As mentioned earlier, classroom teachers regularly collect the type of data I have referred to above.
However, they are sometimes less likely to spend time on systematic organisation or analysis of these
data. This section of the paper provides some relatively simple techniques for interpreting data results
using qualitative methods.
63
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
The first point to be made is that the use of the terms ‘qualitative and quantitative data’ can be
misleading. Data that are often analysed using quantitative techniques such as surveys and tests can
also be analysed qualitatively. Documentary data can provide useful insights into the practices of
teachers and schools, such as timetables, lesson plans, units of work, newsletters and letters to parents,
school policy documents, and texts used in classroom literacy lessons. Lesson observations, interviews,
recorded conversations and interactions between students and teachers are also useful.
In deciding how and what to analyse, it is useful to begin again with your problem or the issue
you want to investigate. The first step in collecting data is to ask: What data are available? This can be
followed by identifying sources of other data to be collected, and then thinking and planning for new
instruments that may need to be produced.
For example, if a classroom teacher wanted to examine the question, ‘Why do the boys in Year
3 complain about reading lessons?’, then she/he could begin with collecting the available data,
including test results, anecdotal records, the teachers’ own reflective journal where there is evidence of
these complaints and/or evidence of the effect of these complaints on student performance, classroom
environment and so on. The teacher might then hold an informal focus group discussion in the
classroom where the students are encouraged to express their opinions about reading lessons, and
she/he could take notes or even record this discussion. The teacher could then decide that a parental
perspective might be useful and write a letter home with two to three questions for parents to answer.
The teacher might ask a teaching partner or colleague to observe reading lessons using a simple
observation schedule that tracked boys’ engagement and interactions.
Once all data are collected, it is important to use some organisational techniques to begin the
analysis and interpretation stages. Sorting, classifying and categorising data helps in the interpretation.
At this stage, some data are discarded, some bits ranked as more important than other bits, some
message or themes are identified and used to develop categories. Patterns begin to emerge, the
most useful often being those identified across more than one data set. Referring back to the earlier
example, it might be observed that parents mention take-home readers frequently; that in anecdotal
records disruptive behaviour is noted at the end of reading lessons when take-home readers are being
organised, and that in the focus group discussion the teacher noted some students complaining
about the take-home readers being ‘boring’. This pattern might then lead the teacher to conduct
some analysis of the take-home reader collection, considering the age, suitability, gendered appeal,
readability and so on.
In literacy classrooms, sometimes the important questions to ask about the data collected are what
could be perceived as the simplest. For example, ‘What are the stories about literacy being told in these
data?’ ‘What counts as literacy in these data?’
Importantly, it is not a search for the ‘right’ or ‘correct’ answer that drives most qualitative data
analysis. Rather, analysis and interpretation of data can provide some possible reasons. It is always
interesting to compare one person’s interpretation with others, making collaborative teacher projects
a worthwhile strategy. Rather than asking ‘What do these data mean?’, it is more useful to ask: ‘What
is a possible story that could be told from these data? What do I think the data mean? What messages
do I hear?’
For example, in one interview, a teacher told me about her first interactions with a new English
curriculum:
64
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
Ann: I came to the first key teaching thing. They were talking about Year 2 Net, and blah
blah blah, and this is in this book, and blah blah blah, this is here, and everyone should
have one, and every teacher should have one. And I went back and said ‘Where are
our books?’ You know, I’ve just been told that every teacher should have this set of
books, and they were all wrapped in plastic in shelves in piles.
This was last year, middle of last year, and I said ‘Right I’ll take my books’ and I took
them, and I unwrapped them. And I took two sets because I was with someone else.
And I took them in and ‘We’re meant to have these’, so we unwrapped them, went,
flicked through them, stuck them on the shelf. ‘Right, we’ve got ours’.
My interpretation of this interview excerpt related to the lines that I have bolded. It appeared to
me that Ann’s initial interest in the texts grew from her knowledge that something was due to her; she
had a right to copies of the texts. The access to the texts was more important than the text itself. Once
access was gained, she had no intention of reading them from cover to cover, or of gaining a secure
working knowledge (which was the intention of the curriculum writers). This interpretation helped me
in my discussion of the relationships between teachers, policy writers, curriculum advisers and the
English curriculum (see Honan 2001).
Someone else, another researcher with a different question or another teacher, or even Ann herself,
might think something else is going on in this excerpt; that there is a different message to hear;
something that I have missed or ignored.
Another example comes from an analysis of a curriculum document (see Rowan & Honan, 2005),
the Early Years Literacy Program (EYLP) in Victoria, which provided teachers with advice about the
structure of their program. This is reproduced in Figure 3.
My interpretation of the messages to teachers embedded in this program included the following
points:
• Literacy is best taught in uninterrupted two-hour blocks of time;
• Reading and writing are two distinct and separate components of literacy that should be
taught separately;
• Speaking and listening learning occurs as part of reading and writing while at the same
time separated from the other modes;
• The organisation of the class in the block is whole class-small group-whole class with
emphasis on individual success and interactivity between groups of children and the teacher.
In workshops and presentations, others have pointed out that the positioning of the words
‘teaching speakers and listeners’ on the side of the figure with no elaboration sends a message that
speaking and listening skills are not important and can be ignored.
Finally, another example of qualitative analysis (also drawn from Rowan & Honan, 2005) is of
an amalgam classroom snapshot. In this snapshot, I drew on multiple classroom observations of
many different classrooms using the ‘Literacy Block’ approach to teaching literacy in the early years.
This snapshot was developed to provide an illustration of the perceived outcomes of the curriculum
program outlined above. In reading this snapshot, I invite you to consider what counts as reading and
writing in this classroom.
The classroom wall clock reads 9.10am. There are about 22 small children sitting cross legged on a
large square of carpet at one end of the classroom. Their posture is largely determined by their distance
from the teacher, who sits on an upright chair in front of the group. So those directly under her gaze
sit straight backed, hands neatly folded in their laps. As the distance grows, so the posture deteriorates
until you find, hidden from the teacher’s gaze by the bodies of the rest of the class, two small boys lying
on their backs. One is quietly humming to himself and rocking his lower body and legs from side to
side, almost as an adult does in a physiotherapy exercise. The other boy is wriggling his whole body in a
snakelike attempt to move closer to his neighbour.
65
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
The teacher’s chair is located close to a blackboard that stretches the width of the classroom. On
one part of the board is a brightly coloured chart, with the heading Task Board, and a table of five
columns and four rows. The days of the week form the headings for the columns. At the beginning of
each row is a pictograph, a symbolised representation of one of the teaching strategies from the EYLP.
For example, guided reading is represented by an image of four heads and a book. There are four
small cards attached to the chart with velcro, and each card holds the image of an Australian animal,
platypus, wombat, kangaroo, echidna.
On the other side of the teacher’s chair is an easel, on which are pinned some large pieces of blank paper.
Leaning against this paper is a large ‘big book’. The teacher is reading the big book to the class. The
class all seem familiar with the text, with some children reading loudly along with her. Two children talk
loudly to each other about what is coming up, describing in some detail to each other the contents of
the following pages. As with the posture of the children, their attention to the book reading seems to
be directly related to their proximity to the teacher. The teacher’s gaze seems to be divided between the
pages of the book she is reading, and those children who sit close to her. There is an invisible circle of
literary appreciation drawn around the teacher and those eight or so children who appear to be enjoying
the reading.
The teacher finishes the reading of the big book and draws the children’s attention to the Task Board.
Figure 3. Excerpt from the Early Years Literacy Program (see Rowan & Honan, 2005, p.204)
66
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
She elicits group and individual responses to her questions from the class. To the two wriggling boys
at the back, she asks: ‘What group are you in Troy and Toby?’ The boys sit up and call back, ‘Wombats
miss!!’ ‘And what will the Wombats be doing this morning?’ After a few seconds of silence, she asks,
‘Can one of the Kangaroos help the Wombats– what will the Wombats be doing this morning, Sarah?’
Sarah, one of the girls sitting directly at the teacher’s feet replies, ‘Reading with you miss.’ ‘Good girl,
Sarah. And what will the Kangaroos be doing?’ There is a choral response as many of the class shout,
‘Sheets!!!’ ‘That’s right, Kangaroos will be working on their worksheets at their desks.’ The other two
groups of children are reminded of their activities (reading from the Book Boxes, and reading with a
parent helper, who is sitting quietly at the back of the classroom, close to the door). The teacher reminds
the class of the rules for the morning: ‘What happens when I’m working with the Wombats, girls and
boys?– what do you have to remember– Echidnas?’ The Echidnas’ responses are varied: ‘Don’t talk to
you’; ‘Stay away!’, ‘Sit in our seats ’til we’ve finished.’ ‘That’s right, good girls, when I’m working with
the Wombats I don’t want to be interrupted, so you read your book quietly, and if you finish reading
your book, what do you do?’ ‘Read it again!’, the Echidnas reply in unison.
The signal to move is almost invisible to the outsider. The teacher merely says, ‘R ight, off we go,’
and many of the children stand immediately and walk purposefully around the room. One girl goes
to a corner and pulls out a large plastic crate filled with ‘levelled readers’. Another girl goes to the
teacher’s desk and collects a cardboard folder with a Kangaroo drawn on the cover. Five children cluster
around the parent helper, who appears not to notice them, as she is bent over her own daughter who
is whispering in her ear. The Wombat group, four boys and two girls remain on the carpet. Some
children sit at desks and pull out pencil cases containing pencils and coloured markers. Within a few
minutes all children seem to be ‘on task’, reading quietly or aloud, writing on worksheets, or responding
to questions from the teacher. There is a ‘working buzz’ in the room. Gradually though the buzz is
subsumed by the sounds of giggles and loud conversations.
The Echidnas have all read their Book Box readers, and have obeyed the instruction to read them
again. All five children have now read their texts twice, and now discard the books. They are giggling,
telling stories; there is the occasional pinch or tweak of an arm or leg.
The Platypus group with the parent helper are taking turns to read aloud from a reader. They too
have finished this ‘round robin’ once, but the parent has begun the reading again. The children who are
waiting for their turn do not follow the text, but whisper to each other.
The Wombats are still working with the teacher, but she seems to find it difficult to hold all their
attention at once– so when she asks one girl a question about the text they are reading, the other five
children appear to be daydreaming.
The Kangaroo group seems to be the quietest, and seems to still all be on task. They have all finished
answering the questions on their worksheets, and are quietly and carefully colouring in the illustrations
that border the sheets.
Occasionally the teacher looks up from her reading and questioning and glances at the wall clock.
At exactly 9.40 am, she stands up and claps her hands in a short rhythmic pattern. The children all fall
quiet, some instantly while others are nudged into silence by their neighbours or by a certain look from
the teacher.
‘R ight, thank you Grade 1s, onto the carpet please’, the teacher commands. While most children
scamper and scramble to reach the carpet square, some detour to return books to the crate, and a small
group cluster around the teacher, eager to inform her of exciting developments during the 20 minute
activity time. She hushes some, listens carefully to a couple, and gives permission for two to go to the
toilet. She then resumes her straight backed chair at the front of the class– this again seems to be an
invisible signal to the class, many of whom begin to try to catch her attention– hands waving frantically
in the air, calling out, ‘Miss, Miss, me please, me!!’ The teacher selects one child, ‘Tanah, your turn
I think today.’ The small girl clambers through the group and stands beside the teacher. The teacher
asks, ‘What did you do today Tanah?’ Tanah replies looking directly at the teacher. During her reply
the teacher gently holds her shoulders in an attempt to direct her gaze towards the class, but Tanah’s
body resists the gentle pushes and swivels around again to look at the teacher. Tanah’s reply seems
well rehearsed; there are phrases within her reply that the teacher mouths silently along with Tanah.
‘This morning, the Kangaroos wrote a lot of B words. Then we wrote our words in sentences. Then we
coloured in our pictures of balls, and baskets and biscuits. Then we packed up our sheets.’ The teacher
asks three other children, representing each of the four groups, to come to the front one at a time. They
each describe the activity engaged with, each using similar words and phrases. The other children sit on
the carpet in much the same positions and postures as they had taken at the beginning of the morning.
The same children sit upright and cross legged close to the teacher and the same two boys lie on their
backs on the edge of the carpet square, hidden from the teacher’s gaze by the other children. (Rowan
& Honan, 2005, pp.213–214)
67
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
My interpretation of what counts as reading in this classroom snapshot included these points:
• Reading involves being organised into small groups;
• Teachers read to the whole class; children read aloud in small groups;
• Reading is writing words beginning with the same consonant;
• Reading is colouring in pictures of words beginning with the same consonant;
• There is a connection between ability to read, and ability to listen to instructions, recall
previous activities, and sit with straight backs and crossed legs (see Kamler, Maclean, Reid
& Simpson, 1992);
• Reading is about reading the same text repeatedly until you are completely familiar with the
text;
• Reading is about gaining operational skills, or being able to draw on codebreaking
resources to make meaning from a text (Freebody & Luke, 2003);
• When we talk about reading, we talk about what we do with texts, rather than our feelings
or understandings of the content of the texts.
Of course there are many other interpretations of this classroom scene, and importantly these
reflect our own ideas, beliefs and values about the teaching of literacy. One interesting exercise could
be for a group of teachers to compare and contrast their views of what is happening in this snapshot.
Conclusion
The push towards collecting large sets of quantitative data seems to be unceasing and unstoppable.
However, ‘big data’ and other forms of quantitative data cannot capture the in-depth and complex
relationships amongst teachers, students, texts and policies that operate within literacy classrooms.
I have provided here some examples of interpretations and analyses of qualitative data that could
be used as models or guides by classroom teachers. Other more structured advice and guidelines
can be found in diverse sources, including textbooks used in postgraduate courses that are available
in university libraries, online professional development courses, professional association workshops,
seminars and conferences. One particular source is that provided in teacher education schools and
faculties at universities. Most of us who work in these contexts are interested and enthusiastic about
sharing ideas for doing classroom-based research with teachers. Importantly, we are interested in
helping teachers gain the research tools required to shape the curriculum to suit their particular
situations and contexts. Collecting, analysing and interpreting qualitative data within a classroom
context sheds significant and in-depth light on the nature of student learning and performance, a light
that cannot be provided solely through the collection of quantitative data or through the analysis of
‘big data’ sets.
References
Australian Council for Educational Research. (2015). Progressive Achievement Tests in Reading (PAT-R)
(Webpage). Retrieved from http://www.acer.edu.au/pat-reading
Australian Council for Educational Research. (2005–2015). Tests of Reading Comprehension (TORCH, 3rd
ed.) (Webpage). Retrived from https://shop.acer.edu.au/acer-shop/group/TORCH-3
Broadfoot, P., Timmis, S., Payton, S., Oldfield, A. & Sutherland, R. (2012). Rethinking Assessment– Learning analytics
and technology enhanced assessment (TEA). Discussion Paper 4. Bristol, UK: University of Bristol. Retrieved from
http://www.bris.ac.uk/media-library/sites/education/migrated/documents/learninganalytics.
pdf
Department of Education, Training and Employment (Queensland). (2005–2015). Frequently asked questions: What
is the School Opinion Survey? (Webpage). Retrieved from http://education.qld.gov.au/schoolopinion
survey/faq.html
Dickens, C. (1961). Hard times. New York, NY: Signet Classic Edition.
68
Literacy Learning:
the Middle Years
Volume 23
Number 3
October 2015
Feinleib, D. (2014). Big data opportunities. In Education big data bootcamp (pp. 173–188). New York, NY:
Apress.
Fleisher, L. (2014). Big data enters the classroom: Technological advances and privacy concerns clash. The Wall
Street Journal. Retrieved from http://www.wsj.com/articles/SB100014240527023047561045794
51241225610478
Freebody, P. & Luke, A. (2003). Literacy as engaging with new forms of life: The ‘four roles’ model. In G. Bull
& M. Anstey (Eds.), The literacy lexicon (2nd ed., pp.51–66). Frenchs Forest, NSW: Pearson Education.
Hawker Brownlow Education. (2012). CARS and STARS (Comprehensive Assessment of Reading Strategies,
and Strategies To Achieve Reading Success) (Webpage). Retrieved from http://www.hbe.com.au/series-
cars-and-stars/cars-how-it-works.html
Honan, E. (2001). (Im)plausibilities: A rhizo-textual analysis of the Queensland English Syllabus. (Doctoral
thesis), James Cook University, Townsville.
Honan, E. (2013). Re-invigorating community-school relations around the teaching of reading. Paper presented
at Brave New World, Australian Association of Teachers of English (A ATE)/Australian Literacy
Educators’ Association (ALEA) National Conference, Queensland University of Technology, July 4–7.
Honan, E., Evans, T., Paraide, P., Reta, M. & Muspratt, S. (2012). Action research booklet for teachers. Brisbane,
Qld: The University of Queensland. Retrieved from http://espace.library.uq.edu.au/view/UQ:320777
Kamler, B., Maclean, R., Reid, J. & Simpson, A. (1992). Shaping up nicely: The formation of schoolgirls and
schoolboys in the first month of school. Canberra, ACT: Department of Employment, Education, and Training.
Langbroek, J-P. (2014). Great results for Queensland in NAPLAN tests [Media statement]. Retrieved from
http://statements.qld.gov.au/Statement/2014/8/18/great-results-for-queensland-in-naplan-
tests
Mayer-Schönberger, V. & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and
think. New York, NY: Houghton Mifflin Harcourt.
news.com.au. (2013). Pisa report finds Australian teenagers education worse than 10 years ago[News article].
Retrieved from http://www.news.com.au/national/pisa-report-finds-australian-teenagers-education-worse-
than-10-years-ago/story-fncynjr2-1226774541525
Ready, D. (2014). Student mathematics performance in the first two years of Teach to One Math. Retrieved from
http://www.newclassrooms.org/resources/Teach-to-One_Report_2013-14.pdf
Pugh, K. & Foster, G. (2014). Australia’s national school data and the ‘big data’ revolution in education
economics. Australian Economic Review, 47 (2), 258–68.
Renaissance Learning. (2015). Renaissance learning (Website). Retrieved from http://www.renaissance.
com/about-us
Rowan, L. & Honan, E. (2005). Literarily lost: The quest for quality literacy agendas in early childhood
education. In N. Yelland (Ed.), Critical issues in early childhood education (pp.197–223). Milton Keynes,
UK: Open University Press.
van Kraayenoord, C., Gillies, R., Honan, E., Moni, K., Western, M. & Brereton, D. (2011). Developing
teachers’ knowledge and pedagogical practices in reading in rural and mining communities. Paper presented
at the Australian Teacher Educators’ National Conference, Valuing Teacher Education: Policy,
Perspectives and Partnerships, Melbourne, Victoria, July 3–6.
Eileen Honan is a Senior Lecturer in Literacy and English Education at The University of Queensland. She
has published in all three of ALEA’s journals, and is a frequent presenter at ALEA National Conferences.
She is an active member of Meanjin Local Council.
Copyright of Literacy Learning: The Middle Years is the property of Australian Literacy
Educators’ Association and its content may not be copied or emailed to multiple sites or
posted to a listserv without the copyright holder’s express written permission. However, users
may print, download, or email articles for individual use.
‘Access to Literacy’ Is Not a Constitutional Right, Judge in Detroit Rules… https://www.nytimes.com/2018/07/04/education/detroit-public-schools-e…
1 of 2 11/18/2019, 6:30 PM
‘Access to Literacy’ Is Not a Constitutional Right, Judge in Detroit Rules… https://www.nytimes.com/2018/07/04/education/detroit-public-schools-e…
2 of 2 11/18/2019, 6:30 PM

Place your order
(550 words)

Approximate price: $22

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
$26
The price is based on these factors:
Academic level
Number of pages
Urgency
Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Read more

Privacy policy

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

Read more