Help with my Methodology Assignment must use the information from articles given, please follow all instructions.

Methodology Assignment

(~2 pages -60 points)

The Methodology section is necessary to describe to the reader what you actually plan to measure/examine in your proposed study. Remember to use future tense are you are proposing a method in which you would collect data given the opportunity.Below, you will find detailed descriptions of each portion of the methodology that must be addressed in this assignment.

Method

Participant/Procedures.

1. Discuss who your intended participants are – be specific and make sure to discuss in this section any inclusion (e.g., must be a full-time graduate student) or exclusion (e.g., individuals attending junior college) criteria for participants.

2. List what personal demographic questions you plan on asking in your survey (e.g., ethnicity, class standing, employment status, etc.). Explain to me why these specific questions matter to you – what is the point of asking them? For example, there is an important distinction between asking for someone’s class standing vs. asking their favorite color.

3. What type of sampling method do you intend to utilize to collect data? Non-Random? Random? Be specific as to why you chose this type of sampling and how it will influence the outcomes of your results.

4. What type of survey design to you intend to utilize? Cross-sectional? Longitudinal? If longitudinal, what specific type of design? In either case, defend why you plan to utilize that design.

5. Include the number of participants you intend to send out your surveyand provide at least two strategies for increasing response rates in the event that you are lacking the adequate number of participants after your initial solicitation.

Quantitative Instruments

Independent Variable (actually use the name instead of this title).This section provides the operational definition of each variable that you used within your survey. You should include information such as official name of scale, number of questions, and an example of one of the questions from the survey. Make sure all information in this section is cited.

Dependent Variable (this will be Student Communication Satisfaction as this is the DV for the entire class).This section provides the operational definition of each variable that you used within your survey. You should include information such as official name of scale, number of questions, and an example of one of the questions from the survey. Make sure all information in this section is cited.

The Development and Validation of
the Student Communication
Satisfaction Scale
Alan K. Goodboy, Matthew M. Martin & San Bolkan1

Four studies (N!639) were conducted to develop and validate a global measure of
student communication satisfaction with an instructor. In study one, participants were
155 students who reported on an instructor from their smallest class during the semester.
Participants completed the Student Communication Satisfaction Scale (SCSS), the
Interpersonal Communication Satisfaction Inventory, and the Conversational Appro-
priateness Scale. Results indicated that the SCSS is unidimensional, has initial
concurrent validity, and is internally reliable. In study two, participants were 161
students who completed the SCSS, Attributional Confidence Scale, Revised Affective
Learning Measure, and Student Motives for Communicating Scale in an attempt to
establish additional concurrent validity. The SCSS was correlated positively with
attributional confidence for the instructor, affect for the course and instructor, and the
relational, functional, participatory, and sycophancy motives, while excuse-making was
correlated negatively with communication satisfaction. Additionally, results of a
confirmatory factor analysis yielded a single-factor solution. In study three, a
confirmatory factor analysis of the scale using another sample (N!165) yielded a
single-factor solution. In study four (N!158), discriminant validity was established as
the SCSS loaded on a separate factor than the ICSI and was correlated positively with a
host of instructional outcomes, student communication behavior, and perceived
instructor communication.

Keywords: Communication Satisfaction; Instructor Communication; Student
Communication; Affective Learning; Motivation

1 Alan K. Goodboy (Ph.D., West Virginia University, 2007) is an Assistant Professor in the Department of
Communication Studies at Bloomsburg University. Matthew M. Martin (Ph.D., Kent State University, 1995) is a
Professor and Chair in the Department of Communication Studies at West Virginia University. San Bolkan is an
Assistant Professor at Bloomsburg University. Alan Goodboy can be contacted at agoodboy@bloomu.edu. The
authors would like to thank the editor, Melanie Booth-Butterfield, and two anonymous reviewers for their
helpful suggestions.

ISSN 0363-4523 (print)/ISSN 1479-5795 (online) # 2009 National Communication Association
DOI: 10.1080/03634520902755441

Communication Education
Vol. 58, No. 3, July 2009, pp. 372″396

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A fundamental characteristic of student”teacher relationships is that student affect
fosters relational development in the classroom (Frymier & Houser, 2000). The

positive development of these relationships is frequently a function of direct

communication between the teacher and student. A plethora of teacher commu-

nication behaviors such as teacher immediacy (Andersen, 1979; Christophel, 1990;

Gorham, 1988; Plax, Kearney, McCroskey, & Richmond, 1986; Richmond, Gorham,

& McCroskey, 1987), teacher confirmation (Ellis, 2000, 2004; Goodboy & Myers,

2008; Schrodt, Turman, & Soliz, 2006), and teacher affinity-seeking (Richmond,

1990; Roach & Byrne, 2001) are behaviors teachers employ to create student affect.

Ultimately, teachers should be concerned with student attitudes and affect as they

relate to actual learning (Bloom, Hastings, & Madaus, 1971; Krathwohl, Bloom, &

Masia, 1964). One affective variable that teachers should be concerned with involves

promoting a feeling of communication satisfaction.
Communication satisfaction is an affective response to the accomplishment of

communication goals and expectations (Hecht, 1978a). Communication satisfaction

results when positive expectations are fulfilled and is largely contextual (Hecht,

1978b). Competent communicators report more satisfaction in communication

encounters (Spitzberg, 1991).
Although research on communication satisfaction has been conducted in other

communication contexts (e.g., Chen, 2002; Myers, 1998), scholars have given little

attention to communication satisfaction in the instructional context (Goodboy &

Myers, 2007; Plax, Kearney, & Downs, 1986). Even though attitudes and affective

learning have received considerable attention in the instructional context (Allen,

Witt, & Wheeless, 2006), communication satisfaction remains a largely under-

studied outcome in the teacher”student relationship. Accordingly, the purpose of
these studies was to develop a measure of student communication satisfaction

with an instructor and begin to validate this affective outcome through validity

testing.

Study One

Hecht (1978a) developed a widely used measure of communication satisfaction called

the Interpersonal Communication Satisfaction Inventory (ICSI). Although Hecht’s

measure has been established as a valid operationalization of interpersonal

communication satisfaction, a different measure may be more appropriate to assess

student communication satisfaction with an instructor for several reasons. First,

Hecht’s measure assesses satisfaction in reference to a particular conversation.

Participants completing this measure reference an actual conversation they recently

encountered. A global measure of student communication satisfaction would allow

assessment in reference to communication with an instructor throughout the

semester. Moreover, some of the scale items in Hecht’s scale are difficult to adapt

globally and irrelevant when measuring global satisfaction (e.g., ‘‘I had something else

to do.’’).

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Second, although the teacher”student relationship is argued to be an interpersonal
one, there are two main characteristics that differentiate it from other relationships:
(a) a lack of equality and (b) a time constraint associated with the relationship
(Frymier & Houser, 2000). Consequently, communication is not as intimate or
personal as in other interpersonal relationships. Much of student communication
with an instructor is centered on gaining information about the course or content

(Martin, Mottet, & Myers, 2000; Martin, Myers, & Mottet, 1999, 2002). This sort of
communication is largely instrumental and does not transpire in other interpersonal
relationships (e.g., romantic relationships, friendships). Thus, fulfilling students’
expectations about communication and eliciting satisfied feelings in the classroom

may not be as personal as some of the items on Hecht’s scale (e.g., ‘‘I felt that we
could laugh easily,’’ ‘‘The other person genuinely wanted to get to know me,’’ ‘‘I felt
like I could talk about anything with the other person’’). Although items such as these
certainly reflect interpersonal communication satisfaction, student communication

satisfaction may not be dependent on perceptions of laughter or the perception that
anything could be talked about. Because research on communication satisfaction
suggests differences in communication satisfaction when relationships are non-
intimate versus intimate (Hecht, Sereno, & Spitzberg, 1984), scale items that reflect
student communication satisfaction should be less interpersonal and, instead, reflect

more of the fulfillment of classroom expectations. Accordingly, the purpose of this
research was twofold: to develop a student communication-satisfaction measure and
to begin validating this measure. Therefore, the following research question and
hypothesis were presented:

RQ1: What is the underlying factor structure for the developed scale and is it
reliable?

H1: A strong correlation will exist between Hecht’s (1978a) interpersonal
communication satisfaction measure and the student communication
satisfaction scale.

Although communication satisfaction can be considered an outcome of commu-

nication competence, interpersonal communication competence is frequently
considered a function of conversational effectiveness and appropriateness (Egland
& Spitzberg, 1996; Spitzberg & Cupach, 1984). Appropriateness refers to when a
behavior does not violate expected norms or values in a given context (Egland &

Spitzberg, 1996). Canary and Spitzberg (1989) examined conflict strategies and
appropriateness and discovered that appropriateness was related positively to
integrative conflict tactics. Self and relational partner perceptions of competence
are strong predictors of effectiveness and appropriateness (Spitzberg, 1991).
Considering that communication satisfaction and conversational appropriateness

both rely on the fulfillment of expectations and are theoretically similar constructs,
they should be correlated positively. In an attempt to establish concurrent validity, the
following hypothesis was posited:

H2: A positive relationship will exist between student communication satisfaction
and reported conversational appropriateness with an instructor.

374 A. K. Goodboy et al.

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Measure Development

The initial step in this study was to develop a global measure of student

communication satisfaction. Twenty-six items were created that assessed general

and global student satisfaction when communicating with an instructor. The first

author created 20 items, which were then reviewed by the second author for face

validity. The second author offered revisions to these 20 items and created an

additional 6 items. These items were created to reflect Hecht’s (1978b) conceptua-

lization of communication satisfaction, this time from an instructional rather than an

interpersonal perspective. To avoid acquiescence response bias, 18 of the items were

positively worded and 8 were negatively worded. These 26 items were administered to

participants. The response format for these items utilized a 7-point Likert-type

format ranging from (1) strongly disagree to (7) strongly agree.
The 26 items from the preliminary pool were subjected to an exploratory factor

analysis (using principal axis factoring). Since a single-factor solution was anticipated,

an exploratory factor analysis was used without rotation of factors. The number of

factors obtained from factor analysis was determined by four criteria. Each factor must

(a) have a minimum Eigenvalue of 1.0, (b) account for at least 5% of the variance, (c)

have a loading of .60 on one factor but less than .40 on another factor, and (d) not cross

load on other factors (Hatcher, 1994; McCroskey & Young, 1979). Two items did not

pass the 60/40 test and were consequently deleted. The remaining 24 items (see Table 1)

produced a single factor with one Eigenvalue greater than 1.0.

Data Analysis

An exploratory factor analysis (without rotation) and internal reliability analysis were

used to test RQ1. Pearson product-moment correlations were used to test H1 and H2.

Results

Research question one inquired about the number of factors in the developed scale

and the reliability of the scale. The exploratory factor analysis (see Table 1) produced

one factor (Eigenvalue!15.81, 65.88% of the variance accounted for; M!5.49,
SD!1.08, Median!5.67, Skewness!#.94) with a total of 24 items. The scale
produced a high internal reliability estimate with an obtained Cronbach alpha of .98.
Hypothesis one predicted a strong relationship between the developed SCSS and

the existing but adapted ICSI. This hypothesis was supported. A positive and strong

correlation was discovered between the two measures (r[154]!.90, pB.001)
accounting for 81% of the variance.1

Hypothesis two examined concurrent validity support by predicting a positive

relationship between the Student Communication Satisfaction Scale and the adapted

Conversational Appropriateness Scale. This hypothesis was confirmed. Results of a

Pearson correlation indicate that this relationship was significant and positive

(r[154]!.56, pB.001) accounting for 31% of the variance.

376 A. K. Goodboy et al.

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Study Two

The purpose of study two was to further validate the Student Communication

Satisfaction Scale (SCSS). Validity refers to whether or not a measure is actually

measuring what is proposed (Kerlinger, 1986). This study focused on establishing

concurrent validity by correlating the SCSS with other established measures with

which it should be theoretically related. Specifically, three variables were chosen to

establish concurrent validity: attributional confidence, affective learning, and student

motives for communicating.

Attributional Confidence/Uncertainty

Uncertainty Reduction Theory (URT; Berger & Calabrese, 1975) proposes that when

strangers first meet, their primary concern is reducing uncertainty, which is

equivalent to increasing predictability. To increase predictability, individuals make

proactive attributions (Clatterbuck, 1979). Proactive attributions are predictions

about future behaviors that an individual may employ, and these predictions are

Table 1 SCSS Items and Factor Loadings

Scale Item (M, SD)
Factor
Loading

1. My communication with my teacher feels satisfying (5.61, 1.26) .83
2. I feel pleased after talking to my teacher (5.54, 1.18) .85
3. I usually feel positive about my conversations with my teacher (5.54, 1.27) .85
4. My teacher makes an effort to satisfy questions I have (5.87, 1.21) .84
5. I get a sense of well being when I communicate with my teacher (5.23, 1.33) .85
6. I feel comfortable talking with my teacher (5.67, 1.30) .73
7. I dislike talking with my teacher (5.83, 1.38) .76
8. I am not satisfied after talking to my teacher (5.72, 1.34) .78
9. My conversations with my teacher are valuable (5.26, 1.40) .76
10. When I talk to my teacher, I feel like it’s a waste of time (5.72, 1.59) .81
11. Talking with my teacher leaves me feeling like I accomplished
something

(5.31, 1.29) .75

12. My teacher fulfills my expectations when I talk to him/her (5.39, 1.35) .86
13. My teacher makes an effort to answer questions I have (5.69, 1.30) .85
14. My conversations with my teacher are worthwhile (5.46, 1.32) .89
15. I wish my teacher was better at communicating with me (5.17, 1.54) .79
16. I feel content when I talk to my teacher (5.35, 1.26) .81
17. I wish my conversations with my teacher were more productive (5.00, 1.69) .78
18. When I talk to my teacher, the conversations are rewarding (5.32, 1.21) .86
19. My teacher makes an effort to satisfy the concerns I have (5.64, 1.27) .86
20. My teacher tends to dominate our conversations and not allow
me to get my point across

(5.39, 1.40) .61

21. I can effectively communicate with my teacher (5.52, 1.30) .79
22. My teacher genuinely listens to me when I talk (5.61, 1.31) .88
23. My teacher can relate to me when I talk to him/her (5.25, 1.32) .73
24. My teacher makes time for me when I want to talk to him/her (5.60, 1.22) .73

Note. Items 7, 8, 10, 15, 17, and 20 are reverse coded. The abbreviated (and preferred) SCSS consists
of items 1, 7, 8, 11, 12, 14, 18, and 19.

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analysis in an attempt to demonstrate the utility of the SCSS in an independent

sample. Furthermore, although studies one and two validated the SCSS in

small classes, study three also sought to validate the SCSS in both small and large

class environments. Therefore, study three assessed a wide array of classes in an

attempt to replicate the dimensionality and the internal reliability of the

abbreviated SCSS.

Method

Participants/Instrumentation

Participants were 165 undergraduate students enrolled in one of eight introductory

or upper-level communication courses at a mid-sized Eastern university.

Participants

were 64 men and 101 women whose ages ranged from 18 to 30 years (M!19.95,
SD!1.72). Thirty five (n!35) participants were freshmen, 79 participants were
sophomores, 17 participants were juniors, and 34 participants were seniors.

Participants completed the 8-item SCSS in reference to their instructor from their

last class during the last week of class (Plax et al., 1986).

Results

Similar to the results in study two, an examination of the data suggested that each of

the variables measured in the scale of student satisfaction was negatively skewed. And,

also similar to study two, we adjusted the data for this pattern of results. Next, the

one-factor model (with error covariances between items seven and eight) was fitted to

the data with the ML method of LISREL 8.8. The model converged and an admissible

solution was obtained. Values of selected fit indices are as follows: x2 (19)!27.81,
p!.09; NC!1.46; CFI!1.00; SRMR!.02; RMSEA!.05. The data from the
analysis suggest that the model fits the data well. All loadings were significant

(pB.05). The obtained Cronbach alpha was .96 (M!4.98, SD!1.68, Median!5.38,
Skewness!#.70).

Study Four

The purpose of study four was to further validate the SCSS. Specifically, this study

sought to establish discriminant validity of the measure by examining the SCSS in

congruence with Hecht’s ICSI, along with similar but distinct instructional outcomes

(i.e., student interest, state motivation, affective learning), student communication

behavior (i.e., out-of-class communication, functional and participatory motives for

communicating), and instructor communication behavior (i.e., teacher confirmation,

teacher clarity). Accordingly, this study sought to differentiate the SCSS from the

existing but adapted ICSI. Additionally, this study examined relationships between

the SCSS and similar constructs to distinguish our operationalization from similar,

yet conceptually different measures.

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significant individuals (Ellis, 2000). Teacher confirmation involves three dimensions:

responding to student questions/comments, demonstrating interest in the student
learning process, and using an interactive teaching style. Students tend to prefer

confirming teachers because they are perceived as understanding, caring, and credible
(Ellis, 2000; Schrodt et al., 2006). Additionally, students report more motivation,

cognitive learning, affective learning, participation, and importantly, student
satisfaction when teachers are confirming (Ellis, 2004; Goodboy & Myers, 2008).

Considering that students report more overall satisfaction with an instructor when
he/she is perceived as confirming (Goodboy & Myers, 2008), it is likely that some of

this satisfaction is a result of rewarding communication encounters. Therefore, the
following hypothesis is posited:

H12: A positive relationship will exist between student communication satisfac-
tion with an instructor and the teacher confirmation dimensions of (a)
responding to questions, (b) demonstrating interest, and (c) teaching style.

Participants

The participants in study four were 158 undergraduate students (53 men, 105

women) enrolled in lower- and upper-level Communication Studies courses at
the same university in study three. Ages ranged from 19 to 46 years (M!21.11,
SD!2.49). Eighteen (n!18) participants were freshmen, 36 participants were
sophomores, 67 participants were juniors, 36 participants were seniors, and 1

participant was unreported. Participants received minimal extra credit.

Procedures and Measurement

Participants completed a survey two weeks before the end of the semester to assess

their communication satisfaction with an instructor along with instructional

outcomes (state motivation, affective learning, student interest), their own commu-
nication behavior (out-of-class communication, functional communication, partici-

patory communication), and perceived instructor communication (teacher
confirmation, teacher clarity). The survey included nine research measures: the 8-

item and 24-item SCSS, the adapted ICSI (Hecht, 1978a), the State Motivation Scale
(Christophel, 1990), the Revised Affective Learning Measure (Mottet & Richmond,

1998), the 18-item Learner Empowerment Scale (LES; Weber et al., 2005) adapted
from Frymier, Shulman, and Houser (1996), Out of Class Interaction Scale (Knapp &

Martin, 2002), two subscales of the Student Motives to Communicate (SMC) scale
(Martin et al., 2000), the Teacher Confirmation Scale (Ellis, 2000), and the Teacher

Clarity Short Inventory (TCSI; Chesebro & McCroskey, 1998). As in study three,
participants again completed the aforementioned measures in reference to their

instructor from their previous class (Plax et al., 1986).
Scale information for the SCSS, ICSI, Revised Affective Learning Measure, and SMC

scale can be found in study two. Because the results of study two suggest the superiority

386 A. K. Goodboy et al.

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of the 8-item SCSS, the SCSS short version was used for this study and produced a
Cronbach alpha of .98 (M!5.04, SD!1.50, Median!5.38, Skewness!#.84). The
ICSI was again modified to measure individual perceptions of global communication
satisfaction with a specific teacher and a Cronbach alpha of .94 (M!4.59, SD!1.25,
Median!4.84, Skewness!#.91) was obtained. The Revised Affective Learning
Measure produced a Cronbach alpha of .97 for both course affect (M!4.76, SD!
1.37, Median!4.90, Skewness!#.62) and instructor affect (M!5.12, SD!1.84,
Median!5.63, Skewness!#.84). The SMC Scale produced a Cronbach alpha of .73
for the functional subscale (M!3.11, SD!.74, Median!3.17, Skewness!#.35) and
.86 for the participatory subscale (M!2.53, SD!.86, Median!2.50, Skewness!.30).
The 18-item LES measures student interest across three dimensions: mean-

ingfulness, competence, and impact. Responses were solicited using a 7-point Likert-
type scale, ranging from (1) completely disagree to (5) completely agree. Previous
reliability coefficients for these subscales have ranged from .81 to .91 (Cayanus &
Martin, 2008; Weber et al., 2005). In this study, obtained Cronbach alphas were .95
for meaningfulness (M!4.78, SD!1.66, Median!5.25, Skewness!#.75), .88 for
competence (M!5.87, SD!1.04, Median!6.00, Skewness!#0.93), and .82 for
impact (M!4.09, SD!1.29, Median!4.17, Skewness!#.21).
The State Motivation Scale is 12 items and asks participants to report on their

levels of state motivation to learn. Responses were solicited using a 7-point bipolar
adjective scale. Previous reliability coefficients have been .93 (Edwards, Bresnahan, &
Edwards, 2008) and .95 (Myers, 2002) for the summed scale. In this study, the
obtained Cronbach alpha was .91 (M!4.22, SD!1.39, Median!4.17, Skewness
!#.08) for the summed scale.

The Out of Class Interaction Scale is 9 items and asks participants to report on how
frequently they engage in out-of-class communication with an instructor. Responses
were solicited using a 5-point Likert scale, ranging from (1) strongly disagree to (5)
strongly agree. Previous reliability coefficients have been .80 (Myers et al., 2005) and .86
(Myers et al., 2007). In this study, the obtained Cronbach alpha was .84 (M!2.60,
SD!0.82, Median!2.56, Skewness!.27) for the summed scale.
The TCSI is 10 items and asks participants to report on the degree to which an

instructor is able to effectively stimulate the desired meaning of course content and
processes. Responses were solicited using a 5-point Likert scale, ranging from (1)
strongly disagree to (5) strongly agree. Previous reliability coefficients have been .86
(Cayanus & Martin, 2008) and .92 (Avtgis, 2001) for the summed scale. In this study,
the obtained Cronbach alpha was .91 (M!3.76, SD!.86, Median!4.00,
Skewness!#.89).
The Teacher Confirmation Scale is 16 items and asks participants to report on the

frequency with which an instructor exhibits confirming behaviors in the classroom
across three dimensions: responding to questions, demonstrating interest, and
teaching style. Responses were solicited using a 5-point Likert scale, ranging from
(1) strongly disagree to (5) strongly agree. Previous reliability coefficients for each
subscale have ranged from .84 to .87 (Ellis, 2004; Turman & Schrodt, 2006). In
this study, obtained Cronbach alphas were .86 for responding to questions (M!4.00,

Student Communication 387

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1

Independent Communication Variable: Parental Academic Support Scale

1. What is the conceptual definition? Cite the actual definition used, do not explain the variable in your own words. (5 points)

Mazer & Thompson (2016) define PASS as “is a multidimensional 16-item measure that assesses the frequency of parent–teacher communication across five dimensions: academic performance (e.g., inquiring about how the child can improve a grade), classroom behavior (e.g., communication about students’ behavior), preparation (e.g., communication about a child’s academic or social preparation), hostile peer interactions (e.g., communication about aggressive encounters between students), and health (e.g., communication about medical issues affecting a child’s work)” (p. 214).

2. Answer the following questions:

a. Indicate which page within the article discusses the operational definition of your variable (2 points)

Page 214

b. Who originally developed this scale? (Hint: You will find this information within the methods section of the article) (2 point)

Joseph P. Mazer and Blair Thompson

c. How many questions are included in the scale? (2 points)

16 Questions

d. Does your scale have dimensions or multiple components that make up the overall variable? If so, what are those dimensions and which items within the scale are associated with those dimensions? (Hint: If multiple dimensions exist, I suggest, using bullets, identify each dimension then provide the items associated). If you believe your variable is uni-dimensional please explain why. (6 points)

· AP = Academic Performance

· CB = Classroom Behavior;

· P = Preparation

· HPI = Hostile Peer Interactions

· H = Health

e. Do any of the items require reverse coding? If so, which items? (2 point)

Parent-teacher contact

f. What are the ranges of scores possible for this scale? In other words, if someone were to complete the scale, what is the highest a participant can score? The lowest? (6 points)

A scale of 1-5 where 5 attract a score of Strongly Disagree while 1 is the lowest that represents strongly Agree

Reference

Mazer, J. P., & Thompson, B. (2016). Parental academic support: A validity report. Communication Education, 65(2), 213-221.

Parental Academic Support: A Validity
Report
Joseph P. Mazer & Blair Thom

pson

This study offers validity evidence for the Parental Academic Support Scale, a 16-item
multidimensional measure that assesses support related to a child’s academic
performance, classroom behavior, preparation, hostile peer interactions, and health.
Confirmatory factor analysis of the Parental Academic Support Scale (PASS) revealed
a close model fit and replicated prior confirmatory factor analysis tests, and
ultimately provided additional evidence for content validity. Correlations between
parental academic support and the Teacher–Parent Contact Scale provided
concurrent validity evidence. More importantly, associations between parental
academic support and a child’s success in school suggest that the PASS construct is
related to other theoretically similar constructs, providing initial evidence for
construct validity. Implications and recommendations for future research are discussed.

Keywords: Parental Academic Support; Success in School; P-12 Level; Confirmatory
Factor Analysis; Validity

Prior research suggests a positive association between parental involvement and
student academic outcomes (Chen, Yu, & Chang, 2007; Cutrona, Cole, Colangelo,
Assouline, & Russell, 1994; Fantuzzo, McWayne, Perry, & Childs, 2004; Rodriguez,
2002; Seitsinger, Felner, Brand, & Burns, 2008). Following this line of research, the
government began a sustained drive to increase parental involvement in K-12 edu-
cation through increased school funding and the implementation of parent-oriented
initiatives and national policies (e.g., The No Child Left Behind Act; Epstein, 1996).
As a result, over the past decade the landscape of parental involvement has
changed, generated the oft-noted “helicopter parent” (Jayson, 2007; Klein, 2008),
and led some school districts to even score parents on their level of involvement
(Jacobson, 2003). One component of parental involvement, parent–teacher

Joseph P. Mazer is an Associate Professor at the Department of Communication Studies, Clemson University.
Blair Thompson is an Associate Professor at the Department of Communication, Western Kentucky University.
Correspondence to: Joseph P. Mazer, Department of Communication Studies, Clemson University, 407 Strode
Tower, Clemson, SC 29634, U.S.A. Email: jmazer@clemson.edu.

Communication Education
Vol. 65, No. 2, April 2016, pp. 213–221

ISSN 0363-4523 (print)/ISSN 1479-5795 (online) © 2015 National Communication Association
http://dx.doi.org/10.1080/03634523.2015.1081957

mailto:jmazer@clemson.edu

communication, has also dramatically changed at the P-12 level (Jacobson, 2003;
Rogers, 2006; Seitsinger et al., 2008; Thompson, 2008). Advances in technology
have transformed parent–teacher communication from interactions at parent–
teacher conferences to, in some cases, weekly contact via e-mail (Thompson, 2008)
and through smartphones (Thompson, Mazer, & Grady, 2015).
In light of recent changes in how parents and teachers communicate and increased

expectations for parental involvement, Thompson and Mazer (2012) developed the
Parental Academic Support Scale (PASS) to assess parent–teacher communication
at the P-12 level. The PASS is a multidimensional 16-item measure that assesses the
frequency of parent–teacher communication across five dimensions: academic per-
formance (e.g., inquiring about how the child can improve a grade), classroom behav-
ior (e.g., communication about students’ behavior), preparation (e.g., communication
about a child’s academic or social preparation), hostile peer interactions (e.g., com-
munication about aggressive encounters between students), and health (e.g., com-
munication about medical issues affecting a child’s work). Across a series of studies
(Thompson & Mazer, 2012), the PASS demonstrated strong reliability and compiled
initial validity evidence, specifically evidence for content validity. Absent from this
line of research is a study that examines the relationship between parental academic
support and other important outcomes such as a child’s success in school. The
present study addresses this gap in the literature and offers important validity evidence
for the PASS by examining it in relation to similar existing measures.

Concurrent Validity

DeVellis (2003) argued that concurrent validity is achieved when a measure correlates
well with a previously validated instrument that assesses the same construct or a differ-
ent, but related, construct. Similar to, but different from, the PASS which measures
actual communication behaviors, the Teacher–Parent Contact Scale assesses how fre-
quently a parent has contact with a teacher either in writing, by telephone, or face-to-
face (Seitsinger et al., 2008). It seems reasonable to argue that parents who communi-
cate academic support for their children through a teacher would also maintain
contact with that teacher.

H1: Parents’ scores on the Teacher–Parent Contact Scale are positively related to
their scores on the Parental Academic Support Scale.

Construct Validity

Construct validity addresses how well a construct fits expected relationships with other
constructs (Suen & Ary, 1989). Through existing theory and research, which serve as
guidelines for expected relationships, assessment of construct validity requires that the
correlations of a particular measure be evaluated in relation to measures for variables
that are known to be related to the construct (DeVellis, 2003). Research suggests a
positive association between perceived parental involvement and student achievement

214 J. P. Mazer and B. Thompson

(Chen et al., 2007; Cutrona et al., 1994; Fantuzzo et al., 2004; Rodriguez, 2002; Seit-
singer et al., 2008). That is, greater perceived parental involvement tends to lead to
greater academic successes for students and more positive perceptions of students’
success in school on the part of parents. Prior research has revealed that parents of
children with borderline grades (e.g., children are close to an A or B) are just as
likely to communicate with teachers as parents whose children are truly struggling
(e.g., on the verge of failing; Thompson & Mazer, 2012; Thompson et al., 2015).
This research also indicates that parents of underperforming students (e.g., failing,
below average, or improving from a B to A grade) are likely to provide greater aca-
demic support to the children. Therefore,

H2: Parental academic support is inversely related to parents’ perceptions of their
child’s success in school.

Method

Participants and Procedures

The participants were 445 parents of students at the elementary, junior high, and high
school levels from a school district in the Midwestern United States. The sample con-
sisted of 90 fathers and 353 mothers (two no reports) with an average age of 40.4 (SD
= 8.1). The sample was primarily Caucasian (94.3%). The majority of parents contin-
ued their education at the college/university level: 10.8% earned an associate’s degree,
38.5% earned a bachelor’s degree, 25% earned a master’s degree, and 6.5% earned a
doctoral degree. Fifteen and one-half percent completed some college, 3.2% possessed
high school diplomas, and .5% completed elementary school. Their children (239
males, 204 females, two no reports) were enrolled in first through 12th grades (elemen-
tary school: N = 169; junior high school: N = 148; high school: N = 128). Many parents
(38.8%) reported that their children were exceptional students (A), 42% indicated
above average (B), 16.3% reported average (C), 2.7% indicated below average (D),
and .2% indicated deficient (F). The researchers obtained institutional review board
and school board approval to survey parents within the district. A list of parent
e-mail addresses was secured from the participating school district. Participants
received the online survey after completing an online informed consent form.

Measurement

Parental Academic Support
Parental academic support was assessed using Thompson and Mazer’s (2012) 16-item
measure (see Table 1). Participants indicated how often each type of support occurred
over the past month by responding on a 5-point Likert-type scale (not at all, once or
twice, about once a week, several times a week, about every day). The scale was reliable:
academic performance α = .88 (M = 9.2, SD = 3.1); classroom behavior α = .77 (M =
3.4, SD = 1.1); preparation α = .84 (M = 2.2, SD = .5); hostile peer interactions α = .84
(M = 2.2, SD = .6); and health α = .84 (M = 2.4, SD = .7). The overall structure of the

Communication Education 215

PASS was tested via confirmatory factor analysis (CFA). All CFA procedures were
conducted using LISREL 8.80, and three popular indices assessed model fit: (a) the
root mean square error of approximation (RMSEA), (b) the nonnormed fit index
(NNFI), and (c) the comparative fit index (CFI). Model fit is generally considered
acceptable if CFI and NNFI values are above .90 (and preferably above .95) and the
RMSEA statistic does not exceed .08 (and preferably .05; Kline, 2005). Following
advice to test multiple theoretically relevant models (Holbert & Grill, 2015; Kline,
2005), we first computed a model comprising the five lower-order latent variables
(academic performance, classroom behavior, preparation, hostile peer interactions,
and health), consistent with prior research in this area. This model demonstrated
close fit, df = 94, RMSEA = .054[90% CI = .047:.063], NNFI = .96, CFI = .97. We then
computed a second model containing a single higher-order latent variable with five
lower-order latent variables. This model produced poor fit, df = 99, RMSEA
= .110[90% CI = −.017:.089], NNFI = .93, CFI = .94, with a chi-square difference test indi-
cating a significant decline in fit relative to the initial model, Δχ2(5) = 15.05, p < .05, suggesting the initial model was appropriate. We also computed a third model con- taining a single latent variable with 16 indicators. This model also yielded poor fit, df = 103, RMSEA = .120[90% CI = −.017:.089], NNFI = .93, CFI = .94, with a chi-square difference test indicating a significant decline in fit relative to the initial model, Δχ2(9) = 19.58, p < .05, suggesting the initial model was appropriate.

Teacher–Parent Contact
Teacher–parent contact was assessed using Seitsinger et al.’s (2008) 12-item scale. This
measure assesses how frequently a parent has contact with a teacher either in writing,

Table 1 Parental Academic Support Scale Items

This past month, I communicated with my child’s teacher about …

1. … my child’s grades in the class. [AP]
2. … why my child has a missing assignment. [AP]
3. … how my child can improve his/her grade. [AP]
4. … why my child received the grade he/she did. [AP]
5. … why my child was not completing assignments. [AP]
6. … learning more about homework assignments. [AP]
7. … a question I had about an assignment. [AP]
8. … solutions to address my child’s behavior in class. [CB]
9. … my child talking back to the teacher. [CB]
10. … my child goofing off in class. [CB]
11. … my child’s ability to make/maintain friendships with peers. [P]
12. … how my child was not bringing materials to class. [P]
13. … my child being picked on by his/her classmates. [HPI]
14. … a major classroom behavioral incident (fight, racial slur). [HPI]
15. … a temporary health issue that my child is experiencing. [H]
16. … a major physical health issue that my child is experiencing. [H]

Note. AP = Academic Performance; CB = Classroom Behavior; P = Preparation;
HPI = Hostile Peer Interactions; H = Health.

216 J. P. Mazer and B. Thompson

by telephone, or face-to-face. Participants responded using a 7-point bipolar scale (1 =
never to 7 = daily). Alpha reliability was estimated at .92 (M = 30.2, SD = 12.6).

Success in School
Parents responded to a three item, 7-point bipolar scale to indicate their perceptions of
their child’s success in school: very unsuccessful/very successful; doing poorly/doing
well; low achieving/high achieving. Reliability was estimated at α = .92 in prior
research (Thompson & Mazer, 2012). In the present study, α = .90 (M = 18; SD = 3.3).

Results

Pearson correlations evaluated the associations between parental academic support
and the Teacher–Parent Contact Scale (H1) and parents’ perceptions of their
child’s success in school (H2). All correlations were corrected for attenuation
(see Table 2). Academic performance (r = .26, p < .01, R2 = .07), classroom behavior (r = .27, p < .01, R2 = .07), preparation (r = .22, p < .01, R2 = .05), hostile peer inter- actions (r = .27, p < .01, R2 = .07), and health (r = .20, p < .01, R2 = .04) were positively related to scores on the Teacher–Parent Contact Scale, supporting H1. Pearson correlations revealed inverse associations between academic performance (r = −.22, p < .01, R2 = .05), classroom behavior (r = −.26, p < .01, R2 = .07), preparation (r = −.16, p < .01, R2 = .03), hostile peer interactions (r = −.18, p < .01, R2 = .03), and health (r = −.11, p < .05, R2 = .01) and parents’ perceptions of their child’s success in school. Therefore, H2 was supported.

Discussion

The present study offers validity evidence for Thompson and Mazer’s (2012) Parental
Academic Support Scale. Confirmatory factor analysis of the PASS revealed close
model fit, replicated prior CFA tests (Thompson & Mazer, 2012), and ultimately pro-
vided additional evidence for content validity. Correlations between parental academic
support and the Teacher–Parent Contact Scale provided concurrent validity evidence.
More importantly, inverse associations between parental academic support and
parents’ perceptions of a child’s success in school suggest that the PASS construct is
related to other theoretically similar constructs, providing initial evidence for con-
struct validity. This finding supports prior research that demonstrates linkages
between parental involvement and student achievement (Chen et al., 2007; Cutrona
et al., 1994; Fantuzzo et al., 2004; Rodriguez, 2002; Seitsinger et al., 2008). The
results indicate that parents of children who are struggling academically tend to com-
municate with the teacher more frequently than parents of children who perceive their
children are excelling in school. The results also indicate moderate relationships
between the five types of parental academic support, suggesting that parents made
appropriate distinctions between the forms of support.
In light of the connections between parental support and perceived student achieve-

ment, the PASS represents an effective tool for teachers, counselors, and

Communication Education 217

Table 2 Descriptive Statistics and Pearson Product-moment Correlations for all Variables

M SD
Academic

Performance
Classroom
Behavior Preparation

Hostile Peer
Interactions Health

Teacher–Parent
Contact Scale

Academic Performance 9.2 3.1 –
Classroom Behavior 3.4 1.1 .36 (.44)** –
Preparation 2.2 .5 .47 (.55)** .50 (.62)** –
Hostile Peer Interactions 2.2 .6 .21 (.24)** .40 (.50)** .41 (.49)** –
Health 2.4 .7 .15 (.23)** .12 (.15)* .18 (.21)** .33 (.39)** –
Teacher–Parent Contact Scale 30.2 12.6 .26 (.29)** .27 (.32)** .22 (.25)** .27 (.31)** .20 (.23)** –
Success in School 18 3.3 −.22 (−.25)** −.26 (−.31)** −.16 (−.18)** −.18 (−.21)** −.11 (−.13)* −.08 (−.09)

Note. Disattenuated correlations appear in parentheses.
*Correlations are significant at p < .05. **Correlations are significant at p < .01.

218
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P
.
M
azer

an
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B
.
T
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om

pson

administrators to assist both parents and their children in the elementary through sec-
ondary school levels. Heeding Seitsinger et al.’s (2008) call for constructing and vali-
dating such a scale, the PASS can assist P-12 administrators in identifying effective
communication topics and behaviors for parents and teachers and, in the end,
better support students. The measure can be used within a school district to identify
the types of parental academic support that are most prevalent and those that are
deficient. School officials can offer practical advice to parents and teachers as well
as potentially implement proactive programs to increase parent–teacher communi-
cation to ultimately enhance parental academic support. Research in this vein can
lead to data-driven parental support initiatives that seek to academically assist P-12
students.
Each study must be interpreted within the limitations imposed by the research

design. First and foremost, the sample primarily consisted of mothers responding
about their female children. Although parents offer the broadest perspective in
terms of the frequency of parent–teacher communication, the fact that the PASS
measures parents’ perceptions of supportive interactions also represents a limitation.
While parents provide the most accurate perspective of parental academic support,
they only offer one perspective; student perspectives are also needed to obtain a
fuller picture of the parental academic support process and establish a more direct
connection between parental academic support and student learning outcomes. This
limitation is especially relevant to the parent-perceived measure of school success uti-
lized in the present study, as a positivity bias might have influenced parents’ percep-
tions of their child’s success in school. Researchers can examine direct connections
between student learning and parental academic support by assessing relationships
between specific types of parental academic support and specific measures of cognitive
and affective learning, student motivation, and student engagement. However, the self-
report nature of these measures can pose data collection challenges for researchers
seeking to study young students, particularly those in elementary school. While
parents’ participation added a unique dimension to the study, their involvement in
the research omitted the opportunity for common student-centered instructional
communication measures (motivation, affective learning) to be utilized. Future
research should seek to couple the participation of parents and students to better
understand the effects of parental academic support on students.
Duration represents another limitation of this study. A one-month time period pro-

vides only a snapshot of the role parental academic support plays in students’ edu-
cational experiences. As Thompson (2008) suggested, parent–teacher
communication differs in terms of frequency across the semester. Longitudinal
research using the PASS can provide a more accurate explanation of the frequency
of parental academic support and offer an opportunity to track students across their
academic experience.
Research indicates a positive relationship between academic support and relation-

ship satisfaction (Mazer & Thompson, 2011). Similarly, parents who regularly com-
municate with their child’s teacher might experience feelings of satisfaction or
dissatisfaction with the degree of support received from the teacher. For instance,

Communication Education 219

parents who routinely communicate with a teacher about their child’s academic per-
formance might feel satisfied with the amount and nature of the support received. On
the other hand, parents may experience feelings of frustration with the quality of com-
munication received from the teacher. Additionally, parents offering academic support
to their children may also experience a stronger relationship with their child through
the support process. Future research can extend our knowledge in these areas.
The PASS measures five dimensions of academic support communicated between

parents and teachers. Although three of those factors contain a relatively small
number of items, the resulting factor-analytic solutions from a series of studies
yielded a concise and well-balanced scale (Thompson & Mazer, 2012). These findings
further confirm the dimensionality of the PASS and offer important validity evidence;
however, future research might explore the relationship between parental academic
support, social support measures (e.g., Barrera, Sandler, & Ramsay, 1981), and par-
ental involvement scales to further validate the PASS. This can provide useful
insight into the important and potentially long-term benefits of academic support
and establish additional validity evidence that supports the PASS as a reliable and
valid tool to assess supportive communication between parents and teachers at the
P-12 level.

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• Abstract

Concurrent Validity
Construct Validity
Method
Participants and Procedures
Measurement
Parental Academic Support
Teacher–Parent Contact
Success in School

Results
Discussion
References