Reprinted from the Journal of Developmental Education, Volume 28, Issue 2, Winter, 2004.
Reading
By Michele L.
Simpson, Norman A. Stahl, and Michelle Anderson Francis
ABSTRACT: Finding practical ideas about college reading
and learning strategy programs that have been drawn from theory and research is
difficult for most veteran instructors, but is even more difficult for those
instructors new to the field. Over a
decade ago the authors reviewed the literature and generated a list of their
own “best ideas” as a way of facilitating professional development. Given the promising research trends and best
practices that have emerged since then, the authors deemed it important to
update these ideas or recommendations.
In addition, the authors have purposely cited many scholarly sources in
order to provide an extensive bibliography for colleagues new to the field.
As the landscape of developmental education and academic assistance continues to shift, both politically and economically, time-honored professionals and those new to the field consistently search for practical ideas they know are embedded in sound theory and research. Although such ideas or recommendations provide many professionals a framework and rationale for their program development, instruction, and program evaluation endeavors, such recommendations are often difficult to unearth, especially for beginners who are less aware of professional organizations and scholarly journals. Over a decade ago we published an article, “Ten Recommendations from Research for Teaching High-Risk College Students,” that was intended to address this issue (Stahl, Simpson, & Hayes, 1992). Given the promising research trends and best practices that have emerged since 1992, we knew it was important to update our original 10 recommendations. After reviewing the literature and discussing important trends with a variety of individuals, we identified 10 recommendations pertinent to the 21st century. In order to provide the most current and relevant research and theory, we decided to direct these recommendations toward instructors who, like ourselves, teach developmental reading and learning strategies courses. To capture that intent we refer to these individuals, our colleagues, as academic assistance professionals.
The first eight recommendations focus on what the extant theory and research suggest in terms of what should be taught and how. The last two recommendations focus on issues involved in successful programs. As we noted in that first article, these recommendations, though not comprehensive, are meant to provide a starting point for discussion and reflection. Moreover, the extensive references in this second article, as they were in the first, are an intentional effort to provide credible sources for future reading. If the original reference list captured the history of the field during the 1980s, this list will serve the same function for the last years of the 20th and the first decade in the 21st century.
In our first article we began by stressing the importance of adopting a
cognitive-based philosophy that emphasizes the development of active learners
who are in control of their learning.
Even though a decade has passed and various models have been advocated
(Farmer & Barham, 2001), this recommendation is still very important and
needs to be revisited during these times of shifting philosophical boundaries
and financially motivated cuts in programs.
That is, a program that aligns itself exclusively to improving students
standardized test scores tends to be more vulnerable to budget cuts by
administrators who view remediation as superfluous and nonessential.
As pointed out by several different individuals, many academic assistance programs still define their delivery model and objectives around state-mandated reading tests (Bower, Caverly, Stahl, & Voge, 2003; Simpson, Hynd, Nist, & Burrell, 1997). Thus, these atheoretical programs emphasize, sometimes exclusively, goals that focus on reading skills that appear on these tests, skills such as drawing inferences, identifying main ideas, and understanding contextual clues. Students typically practice these skills in materials that decontextualize the reading experience to brief narrative or expository passages that are followed by multiple-choice questions, questions similar to the mandated exams (Nist & Holschuh, 2000b). It is acknowledged that such practice may lead to growth on tests while promoting a gatekeeping function, but it must be questioned whether these activities lead students to becoming active readers and learners.
Rather than emphasizing students’ deficits, many academic assistance professionals have found it more advantageous to teach their students to become active, strategic learners. After three decades of research, the field has a rather definitive sense of the characteristics of strategic learners. These characteristics are embedded in theories and models authored by individuals such as Pressley (2000), Weinstein, Husman, and Dierking (2000), and Zimmerman (2000). What these theories share is the belief that reading and studying are dynamic and context-dependent tasks, and active learners have a command of the essential cognitive, metacognitive, and self-regulatory processes. These processes include selecting, summarizing, organizing, elaborating, monitoring, self-testing, reflecting, and evaluating (Nist & Simpson, 2000). When instructors adopt cognitive-based models for their reading and learning strategy courses, they teach their students a repertoire of techniques and strategies that embody these important processes (Alexander, 2004; Winne, 1997).
At first glance it might appear that this
recommendation is a bit ethereal and impractical for the academic assistance
professional facing hordes of students every semester. However, there are many advantages of having
a cognitive-based model that both unifies and guides a program on a long-term
basis. When a program has an encompassing conceptual framework or model,
pedagogical choices such as what materials to buy, what activities to include,
or what program evaluation instruments to use become much easier. Moreover,
when there is a model that guides a program, the objectives become easier to
identify and evaluate. In sum, a
cognitive-based model can provide academic assistance professionals a program
that generates credibility and support on almost any campus, whether it be with
the students, other faculty members, or overly zealous administrators searching
for ways to capture additional sources of money.
Emphasize Strategy Transfer
and Modification Across the Academic Disciplines
The main goal of any academic assistance program is for students to modify and apply the strategies and processes it teaches them to their own academic tasks. As Weinstein et al. (2000) pointed out, “if transfer to other academic coursework and future learning tasks does not occur, these programs are of little value to the students or the institution” (p. 735). Yet, the research suggests that students do not automatically or immediately transfer strategies in a flexible manner (Boylan, 2002; Hadwin, Stockley, Nesbit, & Woszczyna, 2001; Simpson & Nist, 2000). Consequently, academic assistance professionals who are teaching their students how to annotate a textbook or create a map should not be surprised if their students are not using these strategies in their history or biology courses.
According to the extant literature, strategy
transfer and modification can be facilitated if academic assistance
professionals focus on four research-based principles. The first principle stresses that students
will transfer a strategy to their tasks if they possess the “how to employ” or
procedural knowledge of that strategy and the “why and when to use” or
conditional knowledge. For example, with
the preview strategy, students’ procedural knowledge would help them understand
the steps to previewing (e.g., I should read the headings and subheadings and
the introduction) and how to modify those steps when they encounter different
types of texts (e.g., if the text has no boldface headings, I could read the
first sentence of each paragraph).
Students’ conditional knowledge of the preview strategy would help them
understand why previewing is appropriate (e.g., it helps me see the big
picture) and when they should use it (e.g., I should preview before I read or
before I go to a lecture). Research studies have found that conditional
knowledge is especially important to strategy transfer, especially if students
are expected to abandon their usual approaches such as rereading and/or
highlighting that are typically more comfortable and accessible (Hofer, Yu,
& Pintrich, 1998; Weinstein et al., 2000; Winne, 1997).
The second principle states that students’ strategy
transfer takes a sustained amount of time to develop. In other words, students will not immediately
embrace a new strategy and discard their time-honored approaches just because
they heard a brief presentation on studying in college or completed a few
workbook pages. As noted by Hadwin, et al. (2001), strategic learning is
“enacted over time through a series of unfolding events” (p. 10). Hence, it is important to allow for that time
and plan for recursive instruction (Alexander, 2004) by providing for multiple
passes and scaffolding.
The third principle suggests that transfer can be enhanced if students receive explicit instruction. Explicit instruction is characterized by instructors modeling essential reading processes and providing students guided practice in texts that are authentic and represent the kinds of tasks they will encounter during their college career. As noted by Garner in 1990 and reaffirmed 10 years later by researchers such as Schunk and Ertmer (2000) and Pressley (2000), strategy instruction must be embedded within a disciplinary context and should never “occur in a vacuum” (p. 252). In addition, explicit instruction should provide students multiple opportunities for independent practice, prompt and specific feedback on their strategy attempts, and class time for strategy debriefing sessions. During those debriefing sessions students should pose their questions or concerns about a strategy and the instructor and other classmates should offer answers and possible solutions. To illustrate, during a debriefing session on the preview strategy students might ask: (a) Can you preview when your textbook has no boldface headings? (b) Does it take a long time to preview a text? or (c) Can you preview narrative text?
The fourth principle centers on the importance of
teaching students how to reflect on and evaluate their performance and the
strategies or approaches they used in selected learning environments (Campione,
Shapiro, & Brown, 1995; Hubbard & Simpson, 2003; Zimmerman, 2000). Students who are taught how to reflect and
evaluate are the ones more likely to use a strategy and modify it to fit their
tasks (Simpson & Nist, 1997, 2002).
The research also suggests that they will also perform better on exams
(Hubbard & Simpson, 2003). One way
instructors can encourage students to evaluate and reflect is to ask them to
explain how they studied for an exam.
For example, after each exam over a simulation unit, instructors could
ask students, before they see their score and review the actual exam, to answer
the following questions: (a) How long did you study? (b) When did you begin your studying? (c) How did you study? What techniques did you use? (d) What
percentage do you predict you received on the exam? Why do you predict this percentage? After collecting the students’ responses, the
instructor could then analyze the trends and share them with the students,
making sure to emphasize the strategies and plans of A and B students in
contrast to the D and F students. The ultimate goal is for students to evaluate
their performance in terms of their strategic actions or lack thereof rather
than attributing their performance to luck, ability, or the professor.
In sum, this recommendation is dedicated to academic assistance professionals who have struggled with the challenges of encouraging their students to view the strategies they are taught as something productive and useful in their college career. Obviously, strategy transfer and modification are extremely complex and involve far more than good teaching.
The third recommendation addresses the tendency for academic assistance
professionals to focus almost exclusively on a single set of strategies such as
annotating, mapping, or SQ3R rather than the processes embedded in them. Moreover, many course evaluation procedures
ask the students to report on a questionnaire or checklist whether they specifically
employ mapping or annotating during their own reading and studying. If enough students check “yes,” the tendency
is to judge the instruction or unit successful.
Conversely, if students report “no,” the tendency is to feel that the
unit was a failure. Often forgotten in this quest are the underlying processes
embedded in these strategies. As noted
earlier, these cognitive, metacognitive, and self-regulatory processes include
selecting, summarizing, organizing, elaborating, monitoring, self-testing,
reflecting, and evaluating. Ultimately, the goal or touchstone of any program
is for students to develop a personal theory of these essential metacognitive processes
in selecting and using strategies, in a flexible manner, with their own tasks
and texts (Alexander, 2004; Boylan, 2002; Zimmerman, 2000). In other words, it is quite possible that
students may not be choosing to annotate their own textbooks, but they could be
selecting or summarizing when they read.
This is more important than whether the students’ maps look like the
instructor’s maps or whether the students report that they are annotating when
they read and study.
These cognitive, metacognitive, and self-regulatory processes, often
called deep-level processes, have been studied in a variety of ways and have
been linked to students’ academic performance.
Pintrich and Garcia (1994) concluded from their large-scale study at the
Students should not perceive the processes taught to them as fixed,
inflexible entities that are represented in some sort of useless,
time-intensive artifact. Hence, it is
important to make sure that students understand the conditional knowledge of a
strategy and the processes that are embedded in them. For example, when students annotate a text
selection, they should understand that they are selecting, summarizing,
organizing, and monitoring their understanding. Also implicit in this recommendation is that
students need to decipher the academic tasks assigned them by their professors
across the campus. For example, if a
history class requires students to read several sources, understand how the
viewpoints are alike and different, and forge their own generalizations; they
will be involved in deep-level processes such as synthesizing and
elaborating. If academic assistance
professionals have done an exemplary job of teaching, these students would
understand that they have a variety of strategy options that will help them
synthesize and elaborate
for this history course. That is, they
could use charts, study sheets, or maps as they read and study because all of
them are task appropriate.
It is important to remember
that artifacts such as a map or chart are merely that: artifacts. They are merely a means to an end (Hart,
1967). The ultimate end is for students
to have control of the cognitive, metacognitive, and self-regulatory processes
essential to reading, studying, and learning.
Understand the Impact of Students’ Beliefs
about
For our fourth recommendation we turn to an area that has been researched
rather intensively during the past decade: students’ epistemologies or belief
systems. Based on the work of Perry
(1970) and others, these personal theories include students’ beliefs about the
certainty of knowledge, the organization of knowledge, and the control of
knowledge acquisition (Hofer, 2001; Hofer & Pintrich, 1997; Schommer &
Walker, 1995). That is, it is not
atypical for college freshmen to believe that learning should be easy,
completed quickly (i.e., the night before in a cramming session) and should
happen to them because of what others do for them (i.e., the professor did not
teach me how to solve that problem). Hofer (2001) and others have indicated
that students’ theories or beliefs are an aspect of metacognition since the
core definition of an epistemology is knowledge about knowledge and knowing. The extant literature also suggests that
college students have formed their personal theories about reading and learning
by the time they graduate from high school (Hofer & Pintrich, 1997;
Schommer, 1994; Schommer-Atkins, 2002) and that these personal theories are
context specific, varying across academic disciplines (Hofer & Pintrich,
1997).
The impact and relevance of students’ personal belief systems is quite
significant, especially for those academic assistance professionals hoping that
their students will adopt more effective and efficient ways to read and
study. First of all, students’ beliefs
are important because they serve as the filter through which they decipher and
interpret their academic tasks (Nist & Simpson, 2000; Simpson & Nist,
2002; Thomas & Rohwer, 1986). For
example, many college freshmen fail their first chemistry exam because their
beliefs about learning have filtered and reinterpreted their task to be nothing
more than memorizing formulas, a task definition rarely accurate for a college-level
chemistry exam.
Second, it appears from the research literature that students’ beliefs
can influence other factors, such as their motivation, strategy use, and
performance (Hofer, 2001; Schommer, 1994; Schommer-Atkins, 2002). Schommer (1994), for example, found
significant relationships between certain scales on the epistemological
questionnaire she developed and students’ performance and motivation. Simpson and Nist (1997) found some intriguing
trends concerning students’ beliefs in two different case studies conducted in
history courses. Successful students’ (i.e., those who received As and Bs) theories about learning and their theories about what should be
learned in history were very much different from those of the less successful
students (i.e., those who received Ds and Fs).
The successful students seemed to believe that they were totally or
partially responsible for their learning and knowledge acquisition and employed
more task-appropriate and elaborative strategies. In contrast, the less successful students
viewed the professor as the person who not only controlled what they would
learn but also whether they would learn; they also selected strategies that
emphasized rote memorization.
Hence, it is important for academic assistance
professionals to be aware of students’ beliefs or personal theories about
reading and learning. Writing probes (e.g., What does it mean to read?) or case
studies are excellent ways to delineate these beliefs and should be done on a
routine basis if instructors hope to nudge their students’ beliefs about
reading, studying, and learning.
Our fifth recommendation focuses on the critical
role that academic tasks play in terms of students’ strategic learning
(Weinstein, Husman, & Dierking, 2000; Zimmerman, 2000). As noted earlier, contextualization of
strategy instruction is the best approach to help students learn to employ the
strategies and techniques study skills classes teach (Alexander, 2004;
Pressley, 2000). In order to embed
instruction in a context, academic assistance professionals must know that
context or the academic tasks required of their students. Due to its importance, we will examine the fifth
recommendation in two different ways.
First, it is important that academic assistance
professionals understand the academic tasks required of their students (Boylan,
2002). That is, what are the products
that students must produce—tests, papers, projects—in those required core
courses such as biology, history, or geography?
Moreover, what are the processes embedded in those products; do students
have to apply concepts to new situations or merely memorize facts? In order to assist students in transferring
and modifying the processes taught to them, instructors must have a sense of
what their students are encountering outside of the reading or learning
strategy classroom. Such knowledge is
also motivating to students because they realize instructors know what is
happening out there.
Experience suggests that the best ways to understand
the academic tasks at an institution are to discuss these factors with other
professors, observe their classes, and distribute questionnaires that ask
professors to describe their courses and assignments (Burrell, Tao, Simpson,
& Mendez-Burreuta, 1996). Then, armed with that information, instructors
can make sure they are teaching students what they need and provide practices
that reflect the curriculum. To
illustrate, if an instructor learns from a psychology professor that she asks
numerous multiple-choice questions that require students to apply concepts to
new situations, then that instructor can teach students how to locate examples
and to create their own examples. Such
analyses, however, must be done on a regular and recurring manner since faculty
members change, texts change, and standards change.
The second prong to this recommendation is that
academic assistance professionals should teach their students how to decipher
their own academic tasks. Students need
to learn how to define the cognitive, metacognitive, and self-regulatory
processes they will have to employ to complete the exams, papers, and projects
required of them in classes like geography or biology. Stated another way, the goal is to teach
students to be cue seekers who understand the language and metalanguage of the
college curriculum. Interestingly,
research suggests that students who are oblivious to the processes involved in
their tasks or the actual products they must create are the ones who usually
place themselves in academic jeopardy (Hofer, 2001; Simpson & Nist, 1997).
Although there are a variety of ways academic assistance professionals
can help students decipher their academic tasks in their core courses, there
are two that are especially powerful.
First, instructors can teach students how to interpret a syllabus and
how to interact with their professors during office hours. One way to facilitate these tasks is to
provide students with a list of questions to tackle and answer. For example, with the syllabus activity,
students would search for answers to the following questions: (a) How many
pages are you required to read in a week? (b) What types of sources will you be
reading (i.e., primary, multiple)? (c) What is the overlap between the lectures
and assigned readings? (d) What is the exam format (essay, short answer,
objective)? and (e) What is the level of thinking emphasized? Furthermore, students can be taught to
develop hypothetical essay questions based on course objectives for later
study. As more institutions require that syllabi be posted on departments’
homepages, it becomes easier for academic assistance professionals to plan this
type of activity.
In sum, it is important for academic assistance professionals to delineate the academic tasks that their students are being asked to complete in courses such as chemistry and history. Then instructors should teach their students how to understand those tasks so they can make appropriate and effective choices as to how they will read and study.
Many programs still use lists or textbooks that emphasize the rote level memorization of words (Simpson & Randall, 2000). That is, students learn the definitions to words and demonstrate their mastery on multiple choice or matching exams. The problem with such an approach is that students do not understand these words at a deep level, and hence, never incorporate them into their own speaking or writing tasks (Nagy & Scott, 2000; Stahl, 1999). In other words, students take the vocabulary test, leave the classroom, and forget the words. They are doing school but not expanding their vocabularies.
What would be a more research-based approach? The literature suggests that three principles
are particularly important (Blachowicz & Fisher, 2000; Nagy & Scott,
2000; Stahl, 1999). First, instructors
need to place an emphasis on both additive and generative approaches to
building students’ vocabulary knowledge.
Additive approaches focus on building vocabulary knowledge through the
formal study of words that instructors typically provide to their
students. In the past, such an approach
meant that students studied words presented to them in a list. However, the extant literature suggests that
students learn new words more effectively when they are presented and discussed
from a context (Stahl, 1999). That
context might be a psychology chapter, an essay, or a magazine article that the
students have been assigned to read and study.
Moreover, the work of Haggard (1989) and others (e.g., Harmon, 2000)
suggests that students’ input in the process of selecting the words to study
makes the vocabulary building activities even more productive and
engaging. Generative approaches, on the
other hand, emphasize the importance of creating life-long learners of words by
teaching students certain techniques to unlock the meaning of words on an independent
basis. These techniques typically
include how to use the dictionary, how to decipher context clues, and how to
employ prefixes, roots, or suffixes to break down long words such as
“psychoneuroimmunology” (Brozo & Simpson, 2003; Stahl, 1999). Because each of these generative approaches
has inherent advantages and disadvantages, it is wise to keep informed of the
literature. For example, studies done by
McKeown (1990) and Nist and Olejnik (1995) pointed out the many difficulties
students encounter as they attempt to interpret a typical dictionary entry and
use that information to build their word knowledge.
Second, instructors should place an emphasis on expressive language
activities (Francis & Simpson, 2003; Nagy & Scott, 2000) during their
class sessions. Long before students are
asked to write about the words or are tested on the words, they should be given
opportunities to experiment with the targeted words in low-risk
situations. These low-risk sessions
where students “try out” new words should help them learn the correct pronunciation
of a targeted word, the appropriate definitions that fit the context, the
syntactic rules that govern the use of the words, and all the nuances and
connotations connected with the words.
If instructors will frontload their vocabulary instruction in this
manner, students will be more likely to use the words in their own
communication tasks.
Simply
teaching students words is not enough to stimulate true vocabulary growth. Rather, instructors must be cognizant of
principles important to vocabulary instruction and make sure they are
incorporated into their plans and units.
The second process, sourcing, requires students to analyze the sources and to consider how the possible bias of the source might affect the document. Academic assistance professionals could help students analyze primary sources by providing them a list of questions they should ask themselves at the text and chapter level. These questions could include the following: (a) Who is the author and what are his or her qualifications? (b) Are these credentials sufficient to discuss the content presented in the source? (c) Can this information be verified by another source? (d) Is the author’s motivation for writing clear to you? Additional questions similar to these can be located in the extant literature (e.g., Paul & Elder, 2003).
Overall, students need numerous experiences with multiple sources as well as guidance in the questioning and evaluating of such sources. By modeling and teaching appropriate thinking processes, students become prepared for the 21st century where the single textbook paradigm is gradually being overshadowed by an intertextual academic environment drawing upon both traditional text and technology.
Another important characteristic of process-oriented procedures is that they mirror the academic tasks that students must tackle in college (Flippo & Schumm, 2000). Because these procedures focus on the cognitive, metacognitive, and self-regulatory processes involved in active learning and the beliefs and attitudes that students bring to their academic tasks at the college level, they typically have more construct validity than standardized tests. As Perry (1959) pointed out over 40 years ago, “The possession of excellent reading skills as evidenced on conventional reading tests is not a guarantee that a student knows how to read long assignments meaningfully” (p. 199).
Instructors should compile a collection of formal and informal assessment procedures rather than rely on one procedure or measure (Boylan, 2002; Flippo & Schumm, 2000). Although there is not a plethora of formal, published instruments that are process-oriented, the LASSI (Weinstein, Palmer, & Schulte, 2000) is certainly a worthy addition to any program. Academic assistance professionals can also gather a significant amount of data from informal measures that involve students in writing and self-report activities, whether through traditional pen and paper methods or technology enhanced formats (e.g., Blackboard). Writing activities could include autobiographical sketches that students complete at the beginning of the semester and on-going journal entries that require students to monitor, synthesize, and reflect upon their reading and studying (Commander & Smith, 1996; El-Hindi, 2003; Quinn, 2003; Solder, 1998-99). Another option is to use checklists or rubrics as a way to delineate students’ strengths and specific areas of need. For example, checklists that focus on students’ actual lecture notes or textbook annotations provide instructors considerable diagnostic information as to their abilities to note key ideas or sense the relationships between key concepts. Of course, when students analyze their own strategies or those of their classmates, they, too, learn from these process-oriented assessments.
In addition, many academic assistance professionals have historically and routinely found case studies or scenarios to be useful, especially if they are given throughout the semester (Nist & Holschuh, 2000a). At the beginning of the semester a reading instructor could ask students to solve a scenario or problem describing a typical college student. After reading and noting patterns in the students’ answers, the instructor could plan lessons accordingly. For example, it is not atypical for students to recommend to Jason, a character in one of the scenarios, that he should recopy his class notes as the best way to study for an exam. Such a recommendation, of course, is counter to what research has indicated and to what most instructors emphasize in their courses. At the end of the semester the students could then revisit the same scenario, writing again their solutions but without looking back at what they wrote earlier. Students are always amazed at how much they have learned during the semester and how much they have changed in their strategic understanding of the problem.
Scenarios are also incredibly useful diagnostic activities when used in a discussion format whether in the classroom or through a computer-based system such as Blackboard. In order to engage students in thinking about the processes embedded in strategic learning, instructors could assign students to solve a scenario and come to class prepared to discuss their answers. Once the discussion ebbs, students could then write an addendum on what they learned from their classmates and hand in their papers. Instructors who read their students’ solutions and on-line discussions are able to identify their misconceptions and the principles of strategic learning that they did not teach effectively.
Frank Christ (1985) noted several years ago that “any activity worth doing should be evaluated” (p. 3). Hence, our ninth recommendation addresses the characteristics of effective program evaluation endeavors. Program evaluation differs from assessment activities in that the former seeks to describe the overall impact of a program or intervention, such as a required reading strategy course for at-risk freshmen or a summer elective or bridge program for incoming freshmen.
As noted by Boylan and Bonham (2003) and other individuals (e.g., O’Hear & McDonald, 1995), there is a shortage of quality programmatic research on academic assistance programs and courses. The studies that do exist have generally suffered from a series of fatal flaws (Boylan, Bliss, & Bonham, 1997; Koski & Levin, 1998; O’Hear & MacDonald, 1995). More specifically, many program evaluation studies have not been grounded in theory, have not analyzed students’ academic performance using a constellation of dependent variables, and have not examined the critical questions addressing students’ transfer and modification of the strategies to their own academic tasks.
According to the extant literature, valid and
reliable studies have many characteristics, but we will focus on four of
these. First, these studies use
instruments that help answer the why questions about programs, courses, and
interventions (Simpson, 2002). As noted
by Boylan (2002), Weinstein (1994) and others, one of the most common why
questions focuses on students’ growth or change over a period of time and the
factors that may have influenced that growth or change. In contrast, the what questions tend to
examine products or results such as students’ course grades, their retention in
courses and in the institution, their scores on a standardized exam, or their
grade point averages.
Second, effective program evaluation studies use a
combination of theory-based qualitative and quantitative measures, not just the
latter (Boylan, Bonham, White, & George, 2000; O’Hear & MacDonald,
1995). Quantitative measures (e.g.,
standardized reading tests, published questionnaires) have historically been
favored over qualitative measures (e.g., open-ended questionnaires, focus group
sessions, individual interviews) because of the much-publicized limitations of self-report
data (Merriam, 1998; Pajares, 1992). What is often forgotten in these
criticisms of qualitative measures is that quantitatively oriented measures are
equally suspect because they can be narrow in scope, unreliable, or invalid. These particular limitations are typically
present because of the ways in which quantitative instruments, such as
standardized reading tests, are conceived, written, and piloted. Consequently, it makes more sense to use a
combination of qualitative and quantitative instruments so the data from one
can be used to triangulate and provide additional substantiation for the data
gleaned from the other. Moreover,
multiple sources of data enhance the internal validity and reliability of any
research finding (Merriam, 1998).
Third, effective program evaluation
studies should assess the perceptions of the students, the major stakeholders
in this venture (Bradley, Kish, Krudwig, Williams, & Wooden, 2002; Maxwell,
1997). Students have unique insights
into the academic challenges they face which academic assistance professionals
often cannot fully understand. When
students are asked questions about courses or delivery models, they can provide
important data on what worked, and what needs to be improved and why. These types of data are particularly
important to formative evaluation efforts and to the reports that must be
crafted for administrators who are in charge of monies and budgets. Such questioning of students, the
stakeholders, is also a task required by many accreditation agencies.
Fourth, these program evaluation studies need to be conducted over a sustained period of time. As noted by numerous researchers (e.g., Boylan, et al., 2000; Elifson, Pounds and Stone, 1995) and professional organizations (e.g., the American Association of Higher Education, 1992), instructors and administrators should have a long-term plan for evaluating their services and programs. When studies are longitudinal and replicated over time, the internal reliability of the findings will be strengthened. Equally important is to follow the students who use academic assistance services over a period of time (Simpson, 2002). Admittedly, this is an intimidating task given the difficulty in locating former students and encouraging them to participate in a study. Randall (2002), however, was able to overcome these obstacles, conducting a noteworthy study that collected qualitative and quantitative data from 64 students who had taken a learning strategies course. At the time that Randall met with the students, they had taken 3 semesters of course work since their enrollment in the learning strategies course. Obviously, a longer period of time would have been ideal (i.e., 2 years later), but the data Randall collected from these students became extremely useful in a formative and summative manner for that academic assistance program.
Very few
program evaluation studies have incorporated all these four characteristics, but
a study by Weinstein and colleagues (Weinstein, Dierking, Husman, Roska, &
Powdril, 1998) embraces, in an exemplary manner, the spirit of effective
program evaluation research. This study
was grounded in self-regulation theory and was designed to collect data over a
5-year period of time. The researchers
used a variety of methods and instruments to evaluate the impact of a learning
to learn course at the
Given the current political climate, the need for quality program evaluation studies is becoming even more critical. Hopefully, the four characteristics we have outlined will guide administrators and instructors as they design their studies.
Our final recommendation focuses on the need for academic assistance professionals to understand the role that policy has had on our programs and to be proactive as additional policies are proposed and debated. Policy decisions at the federal, state, or local levels have influenced financial support for students and programs, requirements for assessment and evaluation, and mandates for academic standards and rigorous curriculums. Unlike the other nine research-based recommendations, this tenth recommendation has been forged from both experience and observations borne of a long-term perspective on the field of academic assistance.
Influencing policy is not a simple process, particularly when legislators and policy makers believe that the field focuses only on postsecondary level remedial education as an offshoot of the failures in the K-12 schools. Unfortunately, academic assistance professionals have failed to address the policy concerns in two important ways. The importance of policy issues has been overlooked by professionals struggling with more immediate program issues such as scheduling and staffing courses, testing and teaching students, assessing programs, earning tenure and promotion, and participating in shared governance functions. Focusing on policy initiatives may not have always been feasible given time constraints or the reward structure in the academic system. Nevertheless, academic assistance professionals must become part of the policy arena by planning for such activities in state IRA councils and NADE chapters and by working with governmental outreach offices at institutions. The stakes are too high not to be involved.
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