Fluency is “the ability to read accurately, quickly, effortlessly, and with appropriate expression and meaning” (Rasinski, 2005).  It is a necessary component of reading because it indicates that the reader has effortlessly decoded the words.  Successful text decoding is a precursor to comprehension.  As LaBerge and Samuels pointed  out in their 1974 theory of automaticity in reading, readers who must devote a sufficient amount of time and energy to decoding compromise the important task of making sense of the text; comprehension (Rasinski, 2005).  Thus comprehension is negatively affected by a lack of fluency and some researchers may argue that comprehension comes with fluency.  Regardless of whether fluency comes on its own or is a specific strategy that must be taught, one can not dispute that it is a building block of early literacy.

To assess a student’s fluency, timed reading tests are generally given, measuring two components: words correct per minute and reading fluency rate.  The words correct per minute is measured as a percentage of words read correctly from some total number of words, and reading fluency is determined as the number of words read correctly in a given time period, compared with published standards per grade level. The Institute for Literacy has defined  fluency testing as a calculated series of 1-minute tests. The National Reading Panel outlines a procedure for calculating fluency.  It begins with having the administrator select 2 or 3 grade leveled texts (regardless of the student’s instructional level) and have the student read each passage for exactly one minute. vThe administrator counts the number of words read during each test, and computes the average for the number of words read per minute.  Second, the administrator counts the number of words read incorrectly in each passage and computes the average number of errors per minute.  To calculate the average number of correct words read per minute (WCPM) the  administrator then subtracts the average number of errors read per minute from the average total number of words read per minute.  The WCPM rate should then be compared with published standards for fluency at the student’s current grade level (National Institute for Literacy, 2000). 

In 2001 federal funding used to support the No Child Left Behind Act opened the  Reading First Center on Teaching and Learning to support literacy education in Oregon schools.   From that committee the Dynamic Indicators of Basic Early Literacy (DIBELs) assessment was created.  Based on the five big ideas researched and supported by the National Reading Panel,  DIBELs assesses phonemic awareness, alphabetic principle, accuracy & fluency, vocabulary, and comprehension.  In the last 10 years DIBELs has become a household name in the world of early childhood literacy.  Now in it’s 6th edition, DIBELs is used widely across the country; at least 45 states include it as a measure of early childhood literacy skills, but its success does not come without critics (Center for Teaching and Learning, 2010).  DIBELs relies on a method of taking a median score versus a mean, perplexing some critics such as the New York State Education Department which questions “what is the advantage of taking the median score versus the average?”  (Center for Teaching and Learning, 2010).  DIBELs assesses oral reading fluency with a per-selected series of three 1-minute timed tests.   Students are given the text and told to begin reading, while they are timed and scored by an administrator. When 1 minute has passed students are told to stop reading.  The passages are scored for errors, and the total number of words read correctly is recorded as the score.  The median score from the three passages is then recorded as the child’s fluency score.  For example, if the student receives scores of 27, 36, and 25, the recorded score would be 27.  The Dynamic Measurement Group of the University of Oregon maintains that the median score is the most reliable estimate of a child’s performance.  Taking the median score minimizes error in measurement due to extraneous factors such as a child’s background knowledge or interest in particular passage.  Mean versus median is not the only topic of critique DIBELs has received as a method of assessing student fluency.  Miscues and errors in the DIBELs oral reading fluency assessment differs from running records, qualitative reading inventories, and other widely used fluency assessments.

  Running Records, created by reading remedial specialist, Marie M. Clay, assesses oral reading fluency in a way somewhat different from how DIBELs does.  The biggest difference is that DIBELs assess students at a grade level benchmark, whereas various running records can be administered to students regardless of their grade level.  Running Records seek to determine the child’s independent and instructional reading levels, which means a first grader can essentially be administered a fifth grade passage if it is at his independent reading level.  When the passages become too difficult for the child, the instructional level is determined and the test is concluded (Clay, 2000)   Running Records analyze six types of miscues, some are the same as DIBELs while others are vastly different.    While hesitations are not miscued in Running Records, nor are errors in the pronunciation or abbreviations, numerals,  and hyphenated words, there is some miscue analysis in Running Records not recordable as an error by DIBELs assessment.  Most obvious are that all self-corrections are recorded as errors in Running Records.  Similarly, repeated words are ignored and not marked as errors in DIBELs but do count against a student’s score in Running Records.  Substitutions are an additional kind of Running Record error that too is not mentioned in DIBELs oral reading fluency assessment.  A close look at another widely used fluency assessment, Qualitative Reading Inventories, provides another reason to question DIBELs fluency assessment measures.  Essentially, a student could read a single passage have three different administrators score them very differently depending on which fluency measure they were using (Leslie & Caldwell, 2000). 

Additionally, critics of DIBELs have questioned the fairness of the assessment of English Language Learner students and those with disabilities.  In 2008 the Oregon Reading First Center  addressed some the most frequent concerns aiming to dispel myths and rumors of DIBELs assessment.  The Oregon Reading First center proclaimed that DIBELs is an appropriate measure of students for whom English is a second language, unless the student is learning to read in another language.  Furthermore, Oregon Reading First stated that DIBELs is an appropriate measure for all students, even those with Individualized Educational Plans in literacy. The few exceptions are that DIBELs is not appropriate for students that are deaf, have severe disabilities, or have disabilities that affect their speech, such as stuttering, or oral paraxial (Center for Teaching & Learning, 2010).  Although fluency has been identified as an important ingredient in reading, it is only a part of the critical task of being able to read.  Decoding is one part, and comprehension is the other ingredient for success (Griffith & Rasinski, 2004).  Comprehension cannot rely on fluency alone however, it takes practice and skillful use of strategies that work.  There are effective strategies for reading comprehension that are widely recognized as suitable for teaching to young readers and/or less proficient readers in order to improve their comprehension.   Stephanie Harvey and Anne Goudvis, authors of Strategies that Work, have identified 6 key strategies for improving comprehension.  Their strategies, which are geared for K-8 students include activating background knowledge, questioning, visualizing and inferring, determining importance, and summarizing information (Harvey & Goudvis, 2000).   Harvey’s colleague, Debbie Miller,  highlights the same strategies in her book, Reading with Meaning, for the K-3 students.  Miller refers to visualizing as “creating mental images”, and stresses the importance of activating background knowledge through making connections.  Most primary teachers will confirm that their students are constantly making text to self connections, but had more difficulty making text-to-text and text-to-world connections (Miller, 2002).  Activation of background knowledge and making connections are on the forefront of Miller’s strategies for primary-age children, while with explicit instruction, modeling, and a gradual release of responsibility primary students can practice this and the other strategies on their own.   Fisher, Frey, and Lapp describe their experience observing and interviewing 67 nominated, and expert teachers in the field of literacy, who focused on the same reading comprehension strategies promoted by Harvey and Miller.  The findings of their study showed that teachers modeled their own thinking while students were primarily silent observers.  Teachers described their thinking and modeled multiples ways of thinking rather than focusing primarily on one strategy at a time. As one teacher commented, “we need to show students how to incorporate these things automatically and not artificially stop and summarize or question or whatever”. (Fisher, Frey, & Lapp, p. 550).   At the same time, teachers expressed that it is important to not use all of the strategies in their modeling.  In fact, Duke and Pearson assert that each mini-lesson should be kept brief, 10-15 minutes and then gradually move from a position in which the teacher assume all of the responsibility to a situation where the students assume all the responsibility.  This gradual release of responsibility allows the teacher use direct instruction through modeling, followed by guided practice of the strategy to a region of shared responsibility among students and teachers performing the comprehension technique (Duke & Pearson, 2002). To reiterate, DIBELs assesses students on a variety of areas of literacy, including initial sound fluency, letter naming recognition, nonsense word fluency, and oral reading fluency.  Oral reading fluency is the most effective DIBELs measure for assessing oral fluency. DIBELs assesses oral reading fluency at students’ grade level benchmark and compares their scores against benchmark standards.  DIBELs then suggests strategic or intensive interventions for less proficient readers.  In addition to the interventions suggested by DIBELs, comprehension monitoring strategies suggested by experts in the field of literacy, modeled through guided practice and a gradual release of responsibility promote increased comprehension when practiced regularly.  All of these parts of literacy contribute to a balanced and rich early learning environment that will prepare children for success in reading while providing teachers with the assessment tools to teach to where their students are at.

For More Information:

• • Center for Teaching and Learning. (2010). Official DIBELS homepage
  • Clay, M.M., (2000). Running records for classroom teachers. Heinmann.
  • Duke, N. K., & Pearson, D. (2002). Effective practices for developing reading comprehension. In A.E. Farstrup & S.J. Samuels, What research has to say about reading instruction (pp. 205-242). International Reading Association.
  • Fisher, D., Frey, N., & Lapp, D. (2008). Shared readings: modeling comprehension, vocabulary, text structures, and text features for older readers. The Reading Teacher, 61(7), 548-556.
  • Harvey, S., & Goudvis, A. (2000). Strategies that work. Stenhouse Publishers.
  • Leslie, L. & Caldwell, J. (2000). Qualitative reading inventories-3. Pearson Education.
  • Miller, D. (2002). Reading with meaning. Stenhouse Publishers.
  • National Institute for Literacy. (2000). Put reading first: the research building blocks for teaching children to read (PR/Award Number R305R70004). US Department of Education.
  • Rasinski, T. V., Padak, N. D., McKeown, C. A., Wilfong, L. G., Friedauer, J. A., & Heim, P. (2005). Is reading fluency a key for successful high school reading? Journal of Adolescent & Adult Literacy, 48 (1),

It is important to note the variety in type of literacy that occurs in homes. Although on may not realize it, literature appears everywhere. Literature is in the story a picture tells. Like the old saying goes, “a picture tells a thousand words”. Many children are fortune to experience the pleasure of being read to. Children who experience story time learn that print represents words, and words tell an account of something. Children may develop favorite stories and can expect these narratives to be the same each time they are read. Evidence of storytelling’s favorable impact on early literacy is undeniable. “Children who have had many and diver experiences in storybook reading do well on school-based measures of literacy” (Paratore, 57). However, not all children participate in story time experiences prior to a formal schooling experience. “There are other rich and varied literacy and language practices that are embedded in the fabric of children’s daily lives” (Paratore, 57). Though such practices may go unnoticed, a short list of everyday uses of literature and language appears quite impressive. Consider the following uses of everyday language: cutting coupons, reading roads signs, singing songs, filling out a form, cooking from a recipe, perusing the television guide, studying sports scores, balancing a budget, conversation, etc.

Unfortunately, socioeconomic status appears to parallel laying a literacy rich foundation for early literacy skills. “By the age of 3, children in poverty [are] already well behind their more affluent peers” according to a study by G. Wells, 1986 (Waskik and Bond, 63). On the basis of his study, Wells found that lower-income parents placed less value on literacy as evidenced by an absence of books in the home, and lack of rich language use. Not only do children in poverty have less access to literature materials, but their opportunities to converse with adults is 2x-3x lower than that of their middle-class counterparts. Therefore, providing a literacy rich learning environment in the home appears to require access to text, opportunities for read alouds, and meaningful conversation between child and adult.

“Reading aloud to children at home…is probably the most highly recommended activity for encouraging language and literacy” (Beck & McKeown, 2001). Read alouds strength brain development by forcing children to think about more than just the here and now. To make these experiences most effective for children, text must be challenging, and parents must engage in “text talk”, that is “getting children to think about what is going on in the story” (Freppon, p. 144, et al Beck & McKeown, 2001). Talking about text entails asking opened ended questions, activating background knowledge, making comparisons between text and text and/or text and real life, and explaining new vocabulary.

The key to preparing young children for success in learning to read is by providing read aloud experiences coupled with effective text talk. Although it may be relatively easy for middle class parents to provide read aloud experiences for their children, it is not as simple to engage in text talk that promotes language and literacy development. The most common read-aloud strategies are not the most effective. It takes practice on behalf of the parent and child. Use of open-ended questions allows children to construct meaning from what has been. Considering the following questions: “That character’s getting into trouble, isn’t he?” versus “What’s the character doing now?”, the latter probes the listener to construct meaning. Beck and McKeown suggest occasionally waiting to show pictures until after the reading has been discussed. Children often rely too heavily on pictures cues and can misconstrue basic story information when the content of the pictures is in conflict with the text (p 17). “Children need help in bringing background knowledge to bear in appropriate ways”, rather than simply recalling personal experiences, they need to be helped understand how their connection compares with the text. Parents also need to take advantage of the sophisticated vocabulary found in texts, by applying it in conversations with their children. Young children can handle challenging content (McKeown, 10).

In my experiences as an early education educator I have encountered numerous parents that have provided literacy strategies to help their children become successful readers. These parents provided read-aloud opportunities for their children and engaged in successful text talk. Moreover, the culture of their home was a rich literacy environment that included varieties of everyday text, early writing opportunities, singing, phonological activities (rhyming, knowledge of onset & rime), use of rich language, and letter recognition. Although their children knew the alphabet, could print their name, and recognize both upper and lowercase letters, time and time again parents have commented they wished they had spent more time on phonemic awareness. “Phonemes are the smallest units that make up spoken language. English consists of approximately 41-44 phonemes” (Ehri & Nunes). The letters of the English alphabet represent the phonemes in the spelling of words.

Phonemic awareness is a particularly difficult concept to understand. Whereas letter recognition simply implies being able to identify upper and lowercase letters in print, phonemic awareness relies entirely on listening to the units of sounds in spoken language. Many people confuse phonemic awareness with phonics, which is better explained as associating speech sounds with each corresponding letter. Phonemic awareness is difficult because there are more phonemes in the English language than there are letters in the alphabet. Many letter sounds blend together to form a single phoneme which is very difficult to distinguish because “there are no boundaries in speech marking where one phoneme ends and another begins”.

Phonemic awareness is essential for learning to read because of the sheer volume of words in our English language. Occasionally teachers run across a proficient early reader who appears to have mastered decoding, when in reality the students Has simply memorized a considerable amount of sight words. This system of reading may work for a few years, but eventually as the student encounter complex and richer vocabulary, without phonemic awareness skills the reader will fail to advance. While it is true that nearly 85% of the words adults read are sight words, the other 25% must be decoded or sounded out. For one to become a fluent reader, they must understand how to break works into smaller segments and break the code, so to speak.

“Phonemic awareness measured at the beginning of kindergarten is one of the best predictors of how well the child will learn to read during the first two years of school” (Paratore, 2001). Phonemic awareness is equally important in early literacy to write as it is to read. It’s no mystery that writing and reading go hand-in-hand. A beginning writer uses invented spelling by sounding out the smallest pieces of language (phonemes), and putting them into print (Yopp & Yopp, pg 131). The English language is much like a prescription. There is a prescribed spelling and pronunciation for each word dependent on the regularities of phonemes. Although some words with silent letters and unusual spellings defy the rules of the English language, most words can be decoded and spelled correctly simply by having a phonemic awareness and applying it to break words down to the smallest unit of sound.

To reiterate, the most important things parents can do to prepare their children for success in learning to read include providing read aloud experiences coupled with effective text talk. Effective text talk increases a child’s vocabulary and provides essential comprehension strategies such as answering opened ended questions, activating background knowledge, making comparisons between text and text and/or text and real life, and inferring main ideas. In part with providing a literacy rich home environment, parents might consider providing phonological experiences for their child, such as singing songs, playing rhyming games, and teaching children to identify onset and rime. In addition to learning letter names and basic sight word recognition, parents can provide phonics lessons for their children by teaching the sounds associated with each letter. Children who engage in early writing activities such as labeling pictures, and use of invented spellings are practicing phonemic awareness skills by sounding out words and breaking speech into the smallest units of sound for decoding purposes. All of these parts of literacy contribute to a balanced and rich early learning environment that will prepare children for success in school.

Frequency Distributions of the Dependent Variables

In this study, the independent variables include each of the 50 United States including the District of Columbia. In some investigations the four geographical regions of the U.S. are compared.  These regions include the West, Midwest, South, and Northeast.  A breakdown of the states included in each region is given later in this report.  The dependant variables in the continuous data include, but are not limited to: current expenditures per pupil in average daily attendance in public elementary and secondary schools, average pupil/teacher ratio in public elementary schools, estimated average annual salary of teachers in public education, and percent of students in elementary and secondary schools who are eligible for free or reduced-price lunch.  Figure 1 shows the frequency distribution of the current expenditures per pupil in average daily attendance in public elementary and secondary schools, 2005-2006.  Of the 51 states data was collected from, only one state spent less than $7,000.00 per pupil in average daily attendance and that was Utah at $5,960.00. Similarly, only one state spent more than $17,000.00 per pupil and that was the District of Columbia, spending $18,339.00 per pupil in average daily attendance in public school.

Figure 1. Expenditures per Pupil Histogram (thousands of dollars)

Results

Data analysis was compiled using numerous tabular and graphic tables available in Microsoft Office Excel, edition 2007. Figure 1. is a distribution of Expenditures per Pupil (raw scores) shown on the horizontal axis in thousands of dollars spent, with intervals of one thousand dollars along the abscissa. The ordinate indicates the frequency of occurrence by the independent variable, states, along the y axis.

Expenditure per pupil spending in the District of Columbia is an outlier, as indicated in Figure 2., a box plot of expenditures per pupil.  A five-number summary of the data in Figure 2. displays the dispersion of the data, highlighting the minimum and maximum of the data, median expenditure, and the lower (Q1) and upper (Q2) quartile of the data.  The expenditure per pupil for the District of Columbia at $18,339.00 falls beyond the Q2 and could be considered an outlier.

Figure 2. Expenditures per Pupil Box Plot

Distribution of Average Pupil / Teacher Ratio in Public Elementary Schools

Figures 3. and 4. display the distribution of the average pupil to teacher ratio in public elementary schools taken from the fall 2005 school year.

Figure 3. Average Pupil / Teacher Ratio in Public Elementary Schools Histogram

Figure 4.  Average Pupil / Teacher Ratio in Public Elementary Schools Box Plot

Figure 4. shows the corresponding box plot for average pupil / teacher ratio in public elementary schools.  Figure 4. shows the lower whisker, 10.8, is the lowest pupil to teacher ratio in the U.S. in Rhode Island.  The upper whisker score, 20.8, is the highest pupil to teacher ratio, in the state of California.  Utah’s pupil to teacher ratio of 22.8 to 1 is considered an outlier score.

Distribution of Estimated Annual Salary of Teachers in Public Elementary & Secondary Schools

Figures 5. and 6. illustrate the estimated annual salary of teachers in public elementary and secondary schools. The box plot below, show that there are no outliers in state’s wages among teachers.

Figure 5. Estimated Average Annual Salary of Teachers in Public Schools Box Plot, 2005-06.

Figure 6. Estimated Average Annual Salary of Teachers in Public Schools Histogram, 2005-06.

The state with the highest estimated salary is California, at an average of $61,372.00 annually. South Dakota pays its teacher’s the least in estimated annual salary at an average of $35,607.00.

Distribution of Percentage of Students Eligible for Free or Reduced-Price Lunch

            Figures 7. and 8. Display the percentage of elementary and secondary students eligible for free or reduced-price lunch.

Figure 7. Percent of Students Eligible for Free or Reduced Lunch Histogram

Figure 8. Percent of Students Eligible for Free or Reduced Lunch Box Plot

The data illustrated in the histogram shows that only one state has less than a quarter of its students qualifying for free or reduced-price lunch.  That state is New Hampshire, which has 17.70% of elementary and secondary students qualifying for free and reduced-price lunch.  The box plot shows that there are no outliers, and that the state with the highest percentage of free and reduced lunch qualifiers is Mississippi, with nearly 68%.

Frequency Distribution of Categorical Data

            Further statistical analysis was conducted to determine the frequency distribution of the aforementioned dependent variables, by the independent categorical regions. The four U.S. regions include the West, Midwest, South, and Northeast. A breakdown of the states included in each of the four regions is shown in Table 1.

Table 1. U.S. States by Region

Figure 9. is a box plot displaying the frequency distribution of current expenditures per pupil in average daily attendance in public elementary and secondary schools for the 2005-2006 school year.

Figure 9. Expenditures per Pupil by Region

Again, we see that the District of Columbia indicated as the 9th state, listed in alphabetical order, spends over $18,000.00 per pupil, creating an outlier score for the South region.  A closer look at the plot indicates the highest and lowest expenditures per region, as well as the upper and lower quartile for each.

            Figure 10. displays the average pupil to teacher ratio for students in public elementary schools categorized by region, fall 2005.

Figure 10. Pupil / Teacher Ratio in Elementary by Region

Comparing Figure 10. with Figure 4., Utah’s pupil to teacher ratio of 22.10 / 1, is no longer indicated as an outlier when categorized with like pupil to teacher ratios for the additional 12 states in the West region.  In Figure 10. our attention is drawn to the state of Virginia, number 47., in which the pupil to teacher ratio of 11.70 / 1 is considered low comparative to the South region’s other 16 states.

            Estimated annual teacher salary by region, 2005-2006, is shown in Figure 11.

Figure 11. Estimated Average Teacher Salary by Region

While Figure 5. showed no outliers scores in teacher salary nationwide, our attention is again drawn to the South region in Figure 11., where it is evident that three states have an unusually high estimated, annual teacher salary, comparative to other states within the same region. They are, the District of Columbia at an average of $60,526.00, Maryland at $55,738.00, and Delaware at $55,667.00.  Interestingly, Figure 9. showed that the District of Columbia had the hightest expenditure per pupil at an average of $18,339.00.  Figure 11. indicates that D.C. also pays its teachers the highest annual salary, on average.

Figure 12. Percent of Students Eligible for Free / Reduced Lunch by Region

At comparing categorical data within the four regions, Figure 12. illustrates the percentage of students in elementary and secondary public schools who are eligible for free or reduced-price lunch by region, 2006-2007. Again, Figure 8. merits a second look, where it is shown that nationwide there aren’t any outlier states with either high or low free or reduced lunch eligibilities.  However, a study of Figure 12. reveals that New Mexico (state 32), at nearly 61%, has a high percentage of students eligible for free or reduced lunch, compared to the remainder of the West region, which has a median percentage of eligible students under 40%.  Similarly, our attention is drawn to the Northeast, where New York (state 33), also has a much higher percentage of students eligible for free or reduced-price lunch at 43.5%.  Interestingly, the Northeast region also includes the state with the lowest percentage of student eligibility.  New Hampshire (state 30) has an estimated 17.7% eligibility for student free or reduced price lunch.

Statistical and Practical Significance

            Returning to the discussion of expendiures per pupil it can be assumed that since the distance between sucessive scale points are assumed to be equal, money spent is a scale of measurement provided in interval form.  Reflecting on the controversy of amount of money spent yielding higher or lower student success rates, and considering that the research includes the use of post-facto data, a hypothesis of difference requires testing.  The division of the United States into four regions necessitates the use of a one-way Analysis of Variance (ANOVA) or F Ratio statistical test.

Table 2. shows a source of variance for the dependent variable, current expenditures per pupil, per the four U.S. regions. The F ratio was calculated using the sum of the squares, or mean square. The F ratio of 9.75 helps with the goal of analysis of variance to detect the differences among MEANS. The between degrees of freedom (dfb) was calculated using the number of sample groups or regions (4) minus 1. The dfb = 3.  The within degrees of freedom (wdf) was calculated using the total number of scores or states (51) minus the number of groups or regions (4). The within degrees of freedom therefore equals 47.  Using the F ratio of variance between groups divided by the variance within groups, degrees of freedom = (3/48). A table of critical values of F compares the obtained value of F (9.75) with the critical value of F for the appropriate degrees of freedom. For the calculations completed, the column for 3df and the row for 47df intersect at two F values: 2.80 for an alpha level of .05 and 4.22 for an alpha level of .01. The null hypothesis is rejected when the obtained value of F is equal to, or greater than, the critical or table value of F.  Therefore, using a one-way ANOVA, a significant difference was found between the expenditures per pupil, per region.

Table 2. Source of Variance Current Expenditures Per Pupil

            However, it is important to determine where the greatest differences in expenditures per pupil, per region came from. The between-group variance is large, but perhaps it is due to one region spending significantly more than the other regions. Perhaps two or more regions do not differ significantly in their expenditures per pupil at all. Tukey’s Honestly Significantly Difference (HSD) test can be used for this post-hoc comparison of regional spending.  Table 3. provides the data for the post-hoc multiple comparisons test of regional spending.

Table 3. Multiple Comparison Test of Expenditures Between Regions

            From the table, we learn that there are a number of mean differences significant at the .05 level between regional spending. Comparing the West with the Northeast there is a negative difference of $4,356.52 per pupil.  There is a negative difference in the Midwest of roughly $3,700.00 per pupil compared to what is spent per pupil in the Northeast. The South falls short of Northeast spending by roughly $3,880.00 per pupil. But perhaps the most significant mean difference is in the Northeast where at the .05 confidence interval, it can be said that the Northeast is outspending all of the other regions anywhere between $3,700.00 and $4,356,00 per pupil.

            It was determined in Figure 10. Virginia had a low pupil to teacher ratio. Figure 4. showed that Utah’s pupil to teacher ratio was quite high. Regionally comparative, Table 4. provides a look at how the West region has significantly higher pupil to teacher ratios: nearly 3 + students on the average compared to Midwest and Southern classrooms, and more than 5+ students in the West compared to Northeast classrooms. Similarly, compared to the Northeast, Southern classrooms have 2+ students more per teacher.  Overall, the West region has the highest pupil to teacher ratio, with more students assigned per classroom teacher than any of the other U.S. regions.

            With significantly higher pupil to teacher ratios in the West, and significantly higher expenditures per pupil in the Northeast,  annual teacher salaries, especially between these two regions warrant an investigation. Table 5. offers a multiple comparison difference between each of the 4 U.S. regions. Starting in the Northeast where student expenditures are high, annual teacher salaries are only significantly higher than their regional counterparts in the South. However, in Western states where pupil to teacher ratios are higher than all other regions teachers are earning annually an average of more than $6,640.00 less than teachers in the Northeast.  Teachers in the South also earn significantly less than their collegues in the Northeast.   The practical significance of these findings is limited however, as it would have been helpful to have data on cost of living in each region and average educational level of the teachers.

Table 4. Multiple Comparison Test of Average Pupil / Teacher Ratio by Region

Additionally, it is necessary to take a look at the percentage of students eligible for free or reduced lunch, and how their data stacks up regionally. Figure 12.  provided a regional look at socioeconomic statuses; New Mexico, in the Western region, had the largest percentage of students eligible for free or reduced lunch, while New Hampshire, in the Northeast, had the lowest.  In the last multiple comparisons analysis, Table 6. presents evidence that the South has a significantly higher percentage of students eligible for free of reduced lunch than all other regions. In the Northeast, at the .05 confidence interval we see that there are significantly less students eligible for free or reduced lunch than in West and South, by as much as 19%.

Table 6. Multiple Comparison Test of Percentage of Students Eligible for Free / Reduced Lunch

Regional Spending and its Relationship to Academic Success

            Thus far we have looked at how our nationa’s four regions compare with regard to educational spending. Data analysis has been provided for state and regional expenditures per pupil, average teacher salary, pupil to teacher ratios, and socioeconomic status of students between regions.  In attempt to shed light upon the controversy of spending and its association with student success, it is essential to compare the aforementioned data with standardized test scores. The Scholastic Apptitude Test (SAT), a college admissions assessment developed by the United States College Board scores college-bound students in three areas: math, verbal, and writing. Each section of the test is worth 800 points, and the maximum total score is 2400.  Depending upon the type of SAT test taken, the writing portion may or may not be included, thus a total maximum score of 1600 is also possible.  The SAT is a considered fair nationwide and should not present bias based on a student’s geographical region.

            Diagrams A. and B.. present average SAT scores for (A.) Math, and (B.) Verbal, 2005-2006.  Scatter plots of SAT scores versus expenditures per pupil, 2005-2006, are show below.  Diagram A. presents a weak negative correlation. There is some negative slope to the plot indicating that increased expenditures per pupil yield somewhat higher lower math SAT scores. This correlation is rather weak however, and shows almost as much zero correlation between the two variables.

Diagram A. Average Math SAT Scores versus Expenditures Per Pupil

Diagram B. provides more evidence of a negative correlation between expenditures per pupil and average verbal SAT scores.  The negative slope is still rather weak and further analysis must be computed to determine if in fact the correlation is negative, or whether there is zero correlation between SAT scores and expenditures per pupil.  The Correlation Coefficient, or Pearson r is an appropriate statistical test for determining a hypothesis of association between two measures of interval data.  Pearson r can be calculated using the raw data scores in Table 7.

Diagram B. Average Verbal SAT Scores versus Expenditures Per Pupil

Mean math SAT scores are calculated as well as mean verbal, and the mean expenditures per pupil. Using the means the standard deviations can be determined and the data is plugged into the Pearson r equation. The value for the average math SAT score Pearson r = .39 

            To test for statistical correlation degrees of freedom must be obtained for the two variables. Degrees of freedom are calculated using the number of scores minus two. In the SAT math test, 51 scores were obtained, minus two, equals 49.  Using a table for the critical values of r for the Pearson correlation coefficient, the value of r at the .05 confidence interval is .268 and .372 at the .01 confidence interval.  The calculated value of r = .39 and is greater than the table r, thus we reject the null hypothesis, and determine there is statistical association between the two variables. The correlation between math SAT scores and expenditures per pupil is negative!  The same test of statistical significance is used with verbal SAT scores, and too is found to have a negative correlation. The r ratio for verbal SAT scores = .42 where the same number of samples (51) was obtained and r values for the .05 and .01 confidence intervals yield scores of .268 and .372

            It may be useful to determine if a correlation is present between SAT scores and pupil to teacher ratio.  Diagrams C. and D. provide scatter plots of verbal SAT scores, 2005-2006, versus the average pupil to teacher ratio, 2006.  Diagram C shows zero correlation between verbal SAT scores and pupil to teacher ratio. A glance at Diagram D provides the same evidence of zero correlation between math SAT scores and pupil to teacher ratio. Again, calculating the correlation coefficient may present evidence otherwise of either a positive or negative correlation between two of the variable data. 

Diagram C. Average Verbal SAT Scores versus Average Pupil / Teacher Ratio

Diagram D. Average Math SAT Scores versus Average Pupil / Teacher Ratio

Table 8. provides raw data for math and verbal SAT scores and pupil to teacher ratios.

Table 8.  Verbal and Math SAT Scores, Pupil to Teacher Ratio

The number of subjects remain the same (51) – 2 = 49.  Using a table for the ecritical value of r at 49 degrees of freedom yeild values of .268 at the .05 confidence interval and .372 at the .01 confidence interval. The calculated r value = .03 for both math and verbal scores and that is smaller than the table r. Therefore, we must accept the null hypothesis and assume that pupil to teacher ratio has no significant correlation on both math and verbal SAT scores.

            Lastly,  comparing the socioeconomic status of students with their SAT scores may be practical for those wishing to argue that finances significantly impact student success rates. Diagrams E. and F. provide scatter plots for the percentage of students eligible for free or reduced lunch, 2006-2007, versus the math and verbal SAT scores, 2005-2006. A quick look at both scatter plots indicates zero correlation between average math or verbal SAT scores and students’ socioeconomic status.  However, raw data and calculating the product-moment correlation may prove otherwise. Using the data in Table 9.

Diagram E. Average Math SAT Scores versus percentage of students eligible for free / reduced lunch

the number of subjects remain the same (51) – 2 = 49.  Using a table for the critical value of r at 49 degrees of freedom yield values of .268 at the .05 confidence interval and .372 at the .01 confidence interval. The calculated r value = .08 for math and .02 for verbal scores and that is smaller than the table r. Therefore, we must accept the null hypothesis and assume that socioeconomic status has no significant correlation on both math and verbal SAT scores; or does it? 

Diagram F. Average Verbal SAT Scores versus percentage of students eligible for free / reduced lunch

Table 9.  Verbal and Math SAT Scores, Percentage of Students Eligible for Free or Reduced Lunch

Conclusions

            Although all conclusions drawn from the analyses show a lack of positive correlation between financial spending and student success, no direct statement regarding cause and effect can be made. In other words, spending less money on student expenditures & teacher salaries and widening the ratio between pupils and teacher will not cause students to gain higher academic success. Although the data provides a possible hypothesis that more money spent in education correlates with lower levels of academic success, other hypotheses are at least possible. Perhaps a student who scores high on his SAT was encouraged to spend more time studying. Perhaps coming from a low socioeconomic background provides ambition for a child to spend more time studying.  Perhaps teachers with lower salaries are motivated to be highly qualified and teach better than do teachers who are already highly paid. It is important to note that although a relationship may exist, a direct statement on cause and effect cannot be made regarding any of the preceding relationships.

 Lon Thornberg, an assistive technology specialist, conducted a 30 minute interview with Richard Ellenson, CEO and creator of the TANGO. His interview, titled No Limits 2 Learning is podcasted at: BlogTalkRadio.

One of the topics of their interview included a description of how the Tango can be used as an technology tool. The TANGO, an assistive technology communication device, allows students with severe speech impairments, inclusion in the general education classroom. Ellenson conceptualized the TANGO, for his 10-year old son, who has cerebral palsley. In the interview, he chats with a student named Taylor, who too uses the TANGO to communicate. They are joined also by Taylor’s speech pathologist. It is difficult to explain what the Tango looks like, or how it works. I recommend viewing the TANGO website, and trying the online emulator before listening to the podcast, as it will give you an idea of what the computer is like, and how it works. 

Before trying the emulator, think about the three kinds of communication that you incur daily:          

1. Letters and e-mail, of which there is no awareness of user’s speech.
2. Telephone, in which you can hear, but not see the other person
3. Real-time or Live, in which you can see and hear.

Remember that no one using a speech device can ever speak as quickly an able speaker can, in real time. With all communication devices, allow time for the user to formulate their words, which are developing in their brain, much quicker than they can say them.

 Additional Information to Keep in Mind: The podcast references AAC (Augmentative and Alternative Communication), and suggests that users of AAC rarely initiate conversation, but that the TANGO is different, allowing users to be forthcoming. Examples of the alternative AAC might include:  

• gesture and body language
• manual sign
• handwriting
• communication aids

 “Programming language aimed at children that let them create their own interactive stories, games, music, and art.”

 Specifically, Scratch is an application that allows students to mix media to create. In the article, From SuperGoo to Scratch: Exploring creative digital media production in informal learning, Scratch is cited as just one of many tools that speaks to urban youth, and meets the goals of media educators.

 Media educators? My first thought was that this article really did not apply to my job as a kindergarten teacher. Likewise, the majority of my cohorts in continuing education at Seattle Pacific University agreed. However, upon reading more into the article, I realized the purpose was to do more than simply suggest that today’s youth are participating in using multi-media; they are producing it! If you can agree that creative, digital media is going to be a large part of our future, than as an educator, you too should realize the importance of educating tomorrow’s future leaders. Yes, teachers and parents alike are responsible for exploring creating ways of gaining your child’s interests, as well as providing them with the early building blocks that will provide them with the skills to produce.

Produce multi-media? Well, it’s about more than producing media mixes. If you can imagine it, you can produce it. If you can produce it, you can share it. Scratch provides a format in which kids are familiar. Using the background knowledge they have acquired in other subject areas, Scratch allows them to create a project that will be both meaningful to you and to them. At the same time, they will be investing in their future, and creating something that will too interest their peers.

Can Kindergarteners really use Scratch? Training students to use a new application can be challenging, though I’ll wager this concern can be resolved easily. Although Scratch is intended for students ages 8 and up, my class of 5 and 6-year-olds could easily use this application. My half-day kindergarteners spend 30 minutes a week, in a computer lab with a 1:1 ratio of computers to students. The first several months of the school year will need to be reserved for exploration, paired with modeling, by the teacher, in class. After viewing the tutorial, and exploring the Scratch website, I began thinking about the different media projects that could be created using scratch, and how I might relate them to my kindergarten classroom.

The Three Little Pigs – scratched The classic story of The Three Little Pigs is one of our first projects at the beginning of the kindergarten year, Our exploration of various versions of the story include comparing the similarities and differences between different author’s versions, as well as the characters’ houses, the characters themselves, and ultimately how the story ends.

 The Scratch Gallery boasts a number of impressive projects containing retells of The Three Little Pigs. Due to the relevant reading age of the story, the majority of the projects I found were too created by kindergarteners or first grade students. The pictures, videos, and sound clips, were all examples of things I am already doing with my students. Scratch, however, provides an avenue for putting it all together, and sharing it with others. Meanwhile, students are developing proficiency in the kindergarten technology standards.

Lauren Cartier, a classmate of mine, commented on the issue of technology standards as a graduation requirement:

“Some states [require] students to pass a technology course or technology skills test in order to graduate. Either way I think that it is essential that we assess these skills of our students in some way so that we know that the work we are doing as teachers in this area is working.”

I found myself thinking about graduation requirements, quite a bit as I was reading the article on technology integration as it relates to the National Educational Technology Standards. If shown that technological competencies, specifically the six student standards addressed by National Educational Technology Standards, is a requirement for success in the real world, I would agree that knowledge of technology be a requirement for graduation. However, since very few states are yet requiring students to pass computer skills assessment before graduation, it is difficult to know right now, what areas of technology should be taught in schools, let alone assessed and graded (page 491).

I completely agree with my classmate, that technology standards needed assessment as part of a graduation requirement. The assessment of technology standards for graduation should be different however, than are for a teacher assessing her/himself. I don’t believe we can assess ourselves and force our students’ gradations to be dependent upon whether we have succeeded in our teaching or not. I find it a little odd that we have standards in technology, though we do not assess student knowledge of them. As a kindergarten teacher, I find myself teaching the skills, but not assessing them, because there isn’t a grading standard for technology on the kindergarten grading report, in my district. Given that adequate knowledge and use of technology is a prerequisite to success in the post-high school years, a basic operation and social/ethical issues competency exam seems mandatory for candidacy of a high school diploma.

“to cast scorn on teachers for not jumping into new tech like it was a pool of happiness” (Ted Vasel, SPU discussion).

I think the majority of people assume, as I once did, that teachers fail to incorporate higher levels of technology into their curriculum because they are either uncomfortable or don’t know enough about it. Several of my classmates saw this as the veteran teachers’ dilemma. Therefore, young, fresh-out-of-college teachers know technology, feel comfortable with it, and therefore use it, right? Wrong!

As the article continues, we find the disparity between lower-level technology skills and higher-level technology schools parallels a continuum of teacher-centered and student-centered learning. Therefore, we can conclude that teachers incorporate lower-level uses of technology into their curriculums, not because it is easier to use, but because teachers are in control (teacher-centered). A few statistics from the US Department of Education supports this claim. In 2003, well over 83% of teachers surveyed felt prepared enough to use technology in their classrooms. Furthermore, 80% felt as though they were ready to learn more in terms of incorporating higher levels of technology into their classrooms.

If this is all starting to add up, take it with a grain of salt. Because, according to Michigan Virtual University, only 1 in 9 teachers are tech-savvy enough to create a multimedia presentation, and work with spreadsheets & digital software. Moreover, of teachers interviewed, those that do consider themselves tech savvy (the 1 in every 9), feel the pressures of time constraints, lack of resources, and parental complaints.

This leaves me with an important thought on standards, specifically technology standards: we have standards; yes, but are they graded? Can I, as a teacher, justify the use of technology in my curriculum if I am not required to grade students, in their skill level, in this area?

1. Etiquette: electronic standards of conduct or procedure

2. Communication: electronic exchange of information

3. Education: the process of teaching and learning about technology and the use of technology

4. Access: full electronic participation in society

5. Commerce: electronic buying and selling of goods

6. Responsibility: electronic responsibility for actions and deeds

7. Rights: those freedoms extended to everyone in a digital world

8. Safety: physical well-being in a digital technology world

9. Security (self-protection): electronic precautions to guarantee safety

I should note that modeling (the appropriate behaviors) was a recurrent theme among each of the standards, and rightfully so, was also a hot topic within our SPU online discussion.

Of particular interest to me, was the area of ‘Safety’, and its focus on ergonomics. For the purpose of my online discussion with classmates, I reviewed a few articles and found a bit of conflicting information. For example, according to the ISTE, ergonomics, such as carpal tunnel syndrome, eyestrain, and posture are major medical issues that can be linked to computer use. However, according to an article in Wired.com, “In addition to finding a relatively low rate of carpal tunnel syndrome in computer users,” J. Stevens, neurologist, said that there is “no significant differences between computer users who developed the syndrome and those who did not”.

I also explored UCLA’s ergonomics site, for information on general workplace (school place) ergonomics, and discovered on online self-assessment, for anyone who may be physically suffering from technology strains.

Of particular interest in my online conversations was the topic that school districts, (so it seems), are less interested in the issue of ergonomics, as they are with security (i.e.: antitheft). In other words, a hot topic on the discussion boards was the sentiment that school districts are quicker to purchase technology, than they are to fund the cabinets, tables, and chairs that will house the technology. Stationary pieces, such as furniture with anti-theft devices, tend to be more favorable to district personnel funding the decision-making.

Lastly, while it is obvious that varieties of forms of technology are still new, as is our ability to use it appropriately, many schools are finding themselves in the dilemma of the too-much-too-soon syndrome. They are simply unable to keep up with establishing the necessary barriers to make using technology safe.

In the Edutopia article titled “Kids Create and Critique on Social Networks”, a student commented that he posts his work online because others can see his work, and it’s not just in his computer. Some students have even established their own networking sites, such as the Realm of New Thought.

With regard to Instructional Technology Standard 1: Creativity and Innovation, educators can take standards of technology, like Identifying Trends and Forecasting Possibilities and use them with even the most basic pre-school standards, such as keeping a daily weather graph and posting it online. Young students can create graphs, and easily share their work by learning to scan and upload their work to a forum

Researcher, William Richardson says that educational networking sites provide an important avenue for students to share their work, while “[practicing] important soft skills”, such as accepting feedback and usefully reviewing others’ work. I disagree with his statement because although students may be sharpening their technological skills, an online setting provides an atmosphere where critics can allow themselves to be harsh, and presenters less accepting.  In a real time classroom setting, critics should be less harsh, because they are face-to-face with the presenter. Additionally, because the presenter is face-to-face with his critic, would too be more likely to accept the feedback as useful information.

Another important aspect of net critiques especially with young students) involves ongoing modeling by the facilitator. A student mentioned, in our SPU online discussion, that in her real time classroom, elementary students require a lot of modeling in order to give constructive feedback. The same should be true for students posting feedback online.

In keeping up with the times, another topic of our discussions focused on the use of multiple applications of technology. Suddenly following your friends on Facebook, MySpace, and Twitter is a chore, more than a useful tool. With all the innovations in technology, a teacher is now expected to communicate with parents via real time meetings, phone conferences, e-mail, classroom newsletters, classroom websites…Blogs, Twitter, the list goes on. Are we able to keep up with it all?

Lastly, a few tips for networking: whichever application you chose to use, whether it be a networking site deigned for learning, or your own personal website. Be smart about the information you post. Teachers especially need to be careful not to use the names and or pictures or samples of their students’ work without parental permission. Similarly, be watchful about what you say concerning the school and or district, in which you work. Don’t mention the names of parents, coworkers, or other people in your community unless you are willing to reap what may result in its discovery. If you are dealing with a private site, still be cautious as to who you accept as your “friends” or “followers”. Plagiarism may be easier to track with technology, but it is also more readily accessible.

Human Learning and Motivation

Piaget and Vygotsky have both identified that human learning best takes place when learning is student-centered (Santrock, 2001, p369). I believe that there are generally three methods where learning centered on the student, generates new knowledge. Problem-based learning, essential questions, and discovery learning all drive human wisdom. While problem-based learning “emphasizes real-life problem solving…a problem-based curriculum intentionally exposes students to authentic problems like those that crop up in every day life” (Santrock, 2001, p369). Essential questions however, reflect the heart of the curriculum and focus on the most important things students should know. Through asking essential questions, educators often have to plan from a backwards approach, through which teachers create creative inquiries encompassing an entire study, and refer to them throughout the entity of the unit. While essential questions are teacher-driven strategies focusing on student-centered learning, discovery learning completely contrasts direct instruction, because it allows students to construct understandings on their own. John Dewey and Piaget share the similar sentiment that teaching students often takes away from learning. Both believed that students should receive more opportunities to learn on their own (Santrock, 2001, p374).

Whether our learning is teacher directed or discovered independently, I believe the Attribution Theory best describes the phenomenon of what motivates human learning. “The theory assumes that people are inclined to seek information to form attributions” (Schunk, 2004, p352). However, I believe there are numerous motivators that steer human learning. Learning that is formed behaviorally, takes place by repeating behaviors. B.F. Skinner’s Operant Conditioning Theory suggests that we repeat specific behaviors due to an effective reinforcement, whether positive or negative (Schunk, 2004, p19). Motivation can likewise be stressed by environmental conditions. Constructivist Theory suggests that the structure of the learning environment and organization on the part of the teacher and student are complex factors that influence motivation (Schunk, 2004, p306). When considering the Constructivist Theory with regard to motivation, I think of very young students who aim to please their teacher, and those kids are highly motivated to do well, constantly seeking constructive feedback in an effort to produce their best work. Abraham Maslow expanded the Constructivist Theory giving it more humanistic qualities. Maslow’s Hierarchy of Needs suggests that all humans have basic needs, such as safety and a sense of belongingness, and learning cannot take place until these basic needs are met (Schunk, 2004, p336). It is a rarity to find a student completely motivated by intrinsic rewards. Although an interest in learning and the fulfillment of the actual learning experience helps drive our motivation, more often students seek achievement as a source of extrinsic motivation (Schunk, 2004, p376). One form of extrinsic motivation is the “behavior instigated and sustained by people’s expectations concerning the anticipated outcomes of their actions and their self-efficacy for performing those actions” (Schunk, 2004, p360). The Social Cognitive Theory is just one of many forms of motivation that drives human learning.

My Role as a Professional Educator

In my role as a professional educator working with K-6 students, my philosophy of education is influenced by each the behavioral learning theory, social cognitive theory, and information processing theory. The behavioral learning theory works for me in my position as a teacher by stressing the important role the environment has on how I arrange and presented stimuli, and in how I provide feedback (Schunk, 2004, p18). I believe that when working with young learners, behavior management is a key to successfully gaining knowledge. I believe in positive reinforcement, and the behavioral learning theory works for me, by stressing the importance of consistency and providing lots of praise and positive reinforcement. When I provide negative reinforcement, I do so by taking away a negative consequence for good behavior. For example, a student in my class notoriously turns work in late, and makes a positive change by turning his homework in on time. Negative reinforcement of this behavior may allow the student to participate at recess, when in the past he has not been able to do so. The future behavior of the student will be inclined toward his increasingly turning homework in on time.

I’ve found that the social cognitive theory of learning works for me in my role as an educator by encouraging the modeling appropriate behaviors, explanations, and expectations. In an introductory lesson, I will generally implement a guided release of responsibilities model of instruction, which is consistent with the social cognitive theory, by which the teacher “demonstrates, verbalizes, and models thoughts and reasons for performing given actions” (Schunk, 2004, p94). While self-reinforcing statements are useful (statements suchas “I just need to try my best”), I disagree with the cognitive modeling concept of intentionally introducing errors or dilemmas during instruction. Though deliberate mistakes allow students to learn to recognize and deal with difficulties they may stumble upon, since we are all capable of making natural mistakes, I feel it is not necessary to model by error, as it also tends to reinforce negative behaviors. By virtue of the fact that social cognitive theory incorporates observational learning, there are a few requisites to a successful modeling experience. On the part of the student, attention is required, and the teacher should attain to the needs and interests of the students to sustain their concentration. Secondly, retention is key to remembering, so students must have some way of imitating the model once they have observed it. To reproduce a specific behavior, the person must have the necessary motor skills, which is the third condition, and lastly, performances should be encouraged by “direct reinforcements…If a boy sees his neighbor admired for being polite, the boy is likely to imitate him” (Crain, 2000, p195-96).

Information processing is a third theory I find to be consistent with my pedagogical classroom strategies. With regard to memory and learning, I have found that coaching students in implementing effective study strategies aids in long-term memory retention. A reader’s workshop model for literacy instruction emphasizes the importance of arranging thoughts using graphic organizers, asking questions, making connections, and tracking down the important information. The strategies that I teach my students, aid them through the entire stage model of memory, from their attention of the particular learning goal, to their short-term memory, and encoding into the long-term memory. Finally an accurate retrieval of the information learned, too comes from the memory retention strategies of organizing their learning and thoughts. While numerous encoding failures challenge our ability to remember all things learned, teaching students strategies for remembering and studying effectively, motivate learners to want to discover more.

Best Environments for Learning

The National Research Council has expressed the need for various types of learning environments. Each environment is unique and has something to offer to education, but not one environment is sufficient as a sole best practice for learning. Knowledge-centered environments, are preferred by the likes of educator E.D. Hirsch, and those that believe there is a core set of knowledge upon which “knowledge-centered environments take seriously [and] help students become knowledgeable” (National Research Council, 2000, p136). However, knowledge-centered environments must work together with student-centered settings to connect the curriculum to the students’ lives and make it meaningful. I believe both are essential in conjuncture with one another, while student-centered environments allow the learners to make their own discoveries and connections between self, texts, and the world.

I believe environments must be assessment implemented, though not necessarily centered. The heart of education still should focus on the student; the learner, but understanding where the learner is at with regard to the curriculum, requires assessment. “The key principles of assessment are that they should provide opportunities for feedback and revision and that what is assessed must be congruent with one’s learning goals” (National Research Council, 2000, p140). I believe both formative and summative assessments are necessary. In addition, all assessments must fall under the context of being either norm or standards referenced, meaning that the goal is to rank students by level, or to provide an opportunity where it is hoped and expected that all students have the capability and means of meeting mastery. These norm and standards referenced assessments will generally fall under the larger umbrella of formative assessment, in which the goal is to receive and interpret the feedback that will drive further instruction. I believe formative assessments in core knowledge areas provided continuously throughout the year are the best methods in which to learn not only about the students’ thinking, but to analyze the teachers’ skills and ability of meeting every student at their current level. Summative assessments, given at the end of longer units of study, and informal observations also aid in instruction. I believe administering a battery of assessments provide the most thorough opportunities to assess student abilities. Lastly, I believe feedback from assessments shared with parents is most effective, as the parent-teacher team can work better collaboratively to provide the most effective model of instruction for the student.

A final, yet equally important context for student learning involves a community-centered environment. The National Research Council has found that learning environments are richer when there is a “connection between the school environment and the broader community, including homes, community centers, after-school programs, and businesses. Connections to experts outside of school can have a positive influence on in-school learning because they provide opportunities for students to interact with parents and other people who take an interest in what students are doing” (National Research Council, 2000, p147).

Because students spend a relatively small amount of time in class, compared to the amount of time they spend elsewhere, I believe the climate of the classroom community, when connected with home, clubs, and the larger community, is far more enriching that a classroom that operates day in and out disconnected from society. A goal of every educator is to understand how humans learn, which theories and philosophies of education work best in our own teaching, and what environments should we establish to implement the best practices for learning. In my role as a K-6 educator, I have found that human learning is motivated through a variety of contexts, including asking questions, discovery, constructivism, and self-efficacy. In my current assignment teaching a wide range of grade levels, my philosophy of education is influenced by each the behavioral learning theory, social cognitive theory, and information processing theory, all of which have their strengths which work for me, and weaknesses that I choose not to employ. As I have set up my classroom environment for learning, I have tried to make it an atmosphere that is welcoming and consistent with regard to being student-centered, assessment driven, and community based. After an examination of the types of motivation that guide student learning, and the environments with which to implement best practices of teaching I feel that I have established a solid foundation of professional philosophy for my role as a K-6educator.

Crain, W. (2000). Theories of development. New Jersey, Prentice Hall.

Gredler, M. E. (2005). Learning and instruction: Theory into practice. New Jersey, Pearson.

National Research Council (2005). How people learn: Brain, mind, experience, and school.

Washington D.C., National Academic Press.

Santrock, J. W. (2001). Educational philosophy. Boston, McGraw Hill.

Schunk, D. ( 2004). Learning theories: An educational perspective. New Jersey: Pearson.