mathematics efficacy, anxiety and students performance in introductory technology

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CHAPTER ONE
INTRODUCTION
Background to the study
Introductory technology, an important branch within science, is among basic
courses in secondaryschool education curricular. Introductory technology, whose
general content is about using technological tools to solve human problem, is a
subject with a wide coverage. It is important to discover factors affecting the
learning of introductory technology, for increasing efficiency in this course
(Yuksel, 2004). Increase interest in introductory technology today provided
increase importance for introductory technology classes at schools.
Anxiety is described as subjective feeling associated with worries, nervousness
and tension. Anxiety is a complex psychology term including many variables.
Simply put, anxiety is the feelings of worries along with increased vigilance,
increased sympathetic nervous system and difficulty in Government
concentrating (Kelly, 2002). Anxiety is the state of alertness brought up with the
feelings of tension, fear and worries that the people show when they consider
themselves threatened.
Self-efficacy, on the other hand is described as individual jugdement on whether
he/she has the skills to complete a task . In other word, it is individuals own
opinions about whether he/she can achieve. Efficacy believes consists of two
difference structures such as self-efficacy and expectation to get result. Self-
efficacy believe is about individual skills, impacting tasks and expectation to get
results is about the believe that certain actions will results in certain way (Gibson
and Dembo, 2000).

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In Nigeria, as in other countries, there has been a well-recognized, long-term and
precipitous decline in university enrolments in the Science-Technology-
Engineering-Mathematics (STEM) disciplines (Organization for Economic Co-
operation and Development Global Science Forum, 2006; House of
Representatives Standing Committee on Education and Training, 2009).
Concurrently, students choosing to enroll in science-based degree programs are
increasingly poorly prepared in the enabling sciences, including mathematics and
statistics (Brown, 2009; House of Representatives Standing Committee on
Education and Training, 2009). Many education researchers and teaching
academics, lamenting these trends and their multiple consequences, have noted
that a high proportion of students display a pronounced fear or anxiety of
mathematics and/or statistics (Baloglu & Kocak, 2006). Students’ subject choices
reflect their fears as they show an avoidance of subjects that rely on introductory
technology skills or theory (Ashcraft & Krause, 2007; Ashcraft & Moore, 2009).
Yet, at some stage of a science-based degree program, even in the so-called “soft
sciences” such as ecology or environmental science, students need to master
mathematical and statistical skills. It is at this point that the performance of many
otherwise capable students suffer, potentially limiting their academic progression
and career prospects (Brown, 2009; Hembree, 2000). Given the high demand and
low supply of students displaying competence in introductory technology skill
based subjects, it is important that we put systems in place to reverse this
situation.
The long history of research on mathematics anxiety has been previously
summarized by Ashcraft and Moore (2009) and Zeidner and Matthews (2011).
Despite the voluminous literature on the topic over the last thirty years,
contradictions and uncertainties still exist about which students are most likely to
exhibit high levels of mathematics anxiety as against anxiety as a personality trait
or generalized high-stakes test or evaluation anxiety (Mellamby & Zimdars,

3
2010). Gender and age often, but not always, are shown to be significant
predictors of maths anxiety (Andile, 2009; Baloglu, 2002; Baloglu & Kocak,
2006; Sirmaci, 2007) and more recently the level of preparedness or previous
experience of mathematics and statistics emerged as reliable predictors of anxiety
(Ashcraft & Moore, 2009; Baloglu, 2002; Baloglu & Kocak, 2006).
Furthermore, no unifying statements can be easily made about the impact of
mathematics anxiety on student achievement in introductory technology(Kyttälä
& Björn, 2010). High levels of mathematics anxiety often result in impaired
introductory technology performance (Ashcraft & Moore, 2009; Hembree, 2000;
Payne & Israel, 2010). However in a study spanning 41 countries and boasting a
sample size of quarter million students, the impact of anxiety on introductory
technology performance varied significantly amongst different populations (Lee,
2009). Some populations scoring high on the mathematics anxiety scale also
performed well on the mathematics scores of the Program of International
Student Assessment (PISA). Many studies highlight the negative correlation
between mathematics anxiety and efficacy, and students performance in
introductory technology (Ashcraft & Moore, 2009; Hembree, 2000; Payne &
Israel, 2010). Yet others detect an opposite effect: some students, often females,
scoring highly on various anxiety scales in mathematics perform better than
students with low anxiety levels in introductory technology (Mellamby &
Zimdars, 2010). International Journal of Innovation in Science and Mathematics
Education, 20(2), 42-54, 2012. 44.
Unlike most other studies that presumed a linear relationship between academic
performance and anxiety Keeley, Zyac, and Correia, (2008), with strong
theoretical reasoning, hypothesized and subsequently demonstrated a curvilinear
relationship between performance and statistics anxiety amongst secondary
students.

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A review of literature reveals some case studies that investigated the relationship
between self-efficacy, anxiety and the demographic variables such as gender,
grade level, age and attitudes.
Statement of the problem
Students’ performance in introductory technology has reduced due to some
factors like anxiety and efficacy in mathematics. Looking at the rate of failure,
one will come to realize that there is need to look into the problems of
introductory technology in the secondary schools and factors put in place to
check the degree of failure among other reasons. Hence, the need for carrying out
a research on mathematics efficacy, anxiety and its effect on student performance
in introductory technology in selected secondary schools in Lagos State.
Research questions
This study will be designed to answer the following questions:
i. Is there any significant relationship between student’s age and academic
performance on mathematics in introductory technology?
ii. Is there any significant relationship between student’s attitude and
academic performance on mathematics in introductory technology?
iii. Is there any significant relationship between student’s grade level and
iv. Is there any significant relationship between student’s gender and

5
Significant of the study
Improved student’s performance in introductory technology has tremendous
value on educational system of any nation. This research will therefore be of
great assistance to education administrators, planners, policy makers, parents
even the society to know the implications of mathematic efficacy and anxiety on
students performance in introductory technology.
Also, the study will educate parents and teachers on how to monitor the students
in order to improve their performances in introductory technology.
Finally, the study will serve as basis for further research.
Scope of the Study
This study is expected to cover all the Junior Secondary Schools in Alimosho
Local Government Areas in Lagos State. But it has been limited to cover five of
the schools because of time and financial constraints.
Operational definition of terms
The researcher found it necessary to define some major terms to aid the
understanding of the research work. Some of the terms include:
a. Mathematics: a science (or group of related sciences) dealing with the
logic of quantity and shape and arrangement.
b. Efficacy: capacity or power to produce a desired effect.

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c. Anxiety: a relative permanent state of worry and nervousness occurring in
a variety of mental disorders, usually compulsive behavior or attacks of
panic.
d. Performance: the act of performing; of doing something successfully;
using knowledge as distinguished from merely possessing it.
e. Technology: the practical application of science to commerce or industry.

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CHAPTER TWO
REVIEW OF RELATED LITERATURE
This chapter deals with the review of related literature in respect of
mathematics efficacy, anxiety and student performance in introductory
technology in Lagos State and will be examined under the following
subtopics:
a. Mathematics instruction
b. Mathematics anxiety
c. Efficacy in mathematics
d. Student attitudes to mathematics
e. Manipulative methods (solving mathematic efficacy and anxiety)
f. Technology
g. Student experience in mathematics anxiety and efficacy
Mathematics Instruction
Mathematics instruction was previously viewed as the teacher holding the
answers and instructing the students using rote methods requiring
memorization. In a study entitled, Expanding the Scope of Mathematics
Instruction, Amy Rose (2000) indicated that the teaching of mathematics has
shifted over the years. Mathematics educators are calling for a more student-
centered approach (constructivism) in their teaching enabling students to
construct their own meaning of math problems (NCTM, 2000).

8
The constructivist view on teaching and learning is that education should be
student-centered, and that the teacher’s role is not to transmit information
(Alkove & McCarty, 2000). Alkove and McCarty (2000) further state that
constructivist classrooms are areas of discovery by the students, where they
are learning mathematics by manipulating figures and forms. Moyer and Jones
(2004) espouse the same idea of instruction in the mathematics classroom.
“Ideally, in the 21
st
century mathematics classroom, control of mathematics
tools and decisions to use them should be shared within a guided framework”
(p.17). Thus illustrating the essentials of a constructivist classroom where the
students have a say in what is learned and the manner in which it is learned.
In a study comparing constructivist and traditional Instruction, Alsup (2004)
created a picture of a classroom of students grasping for pattern blocks, rulers,
calculators, and even a computer to justify their solution. In turn, another
picture was painted of a classroom where students were memorizing steps of a
teacher-directed algorithm and practicing a litany of procedures (Alsup,
2004). The students who were given the tools to justify their solution had
ownership of their answer and knew how they had derived the answer. The
two classrooms vary drastically and the effect on the students’ acquisition of
mathematical knowledge is considerably different.
In Alsup’s (2004) study, the group of students who were instructed under the
constructivist style of instruction became less anxious about mathematics,
more confident in their ability to teach it, and more empowered with regard to
their own learning. In regards to instructional styles, Von Glasserfeld (2000)
asserts that all too frequently the present ways of teaching mathematics
generates in the student a lasting aversion against numbers, rather than an

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understanding of the useful and sometimes enchanting things one can do with
them. When the students who participated in Alsup’s (2004) study were
interviewed, many spoke positively toward constructivist teaching and
learning. Many said that they preferred the constructivist instructional
approach to a more traditional one because they have learned more
mathematics, were more involved, and had a more pleasant experience.
Much of the mathematics anxiety present in students has roots in the teachers
and teaching of mathematics (Fiore, 2000). Educators today are challenged
with the choice of utilizing the most effective and beneficial method of
instruction for their students. The National Council of Teachers of
Mathematics, NCTM (2000) espouses that the kinds of experiences teachers
provide clearly play a major role in determining the extent and quality of
students' learning. In an effort to reduce mathematics anxiety in students,
researchers have evidence that supports the growing use of hands-on activities
in the classroom.
Mathematics Anxiety
The construct of ‘mathematics anxiety’ has received considerable attention
from researchers in the past few years (Newstead, 2000). Mark H.(2002)
defined mathematics anxiety as a phenomenon that is often considered, when
examining students’ problems in mathematics. He also defines it as a feeling
of tension, apprehension, or fear that interferes with math performance. In the
article, Anxiety and Mathematics: An Update, Tobias and Weissbord (2000)
define mathematics anxiety as the panic, helplessness, paralysis, and mental
disorganization that arises from some people when they are required to solve a
mathematical problem.

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The feeling of anxiety and tension associated with mathematics is an
extensively studied and universally understood topic. In a more general
definition, mathematics anxiety has been defined to be a state of emotion
underpinned by qualities of fear and dread to perform mathematically. This
feeling has gripped many students into the belief that they are unable to be
successful in mathematics courses.
Ashcraft (2002) suggests that highly anxious students will avoid situations in
which they have to perform mathematical calculations. Unfortunately, math
avoidance results in less competency, exposure and math practice, leaving
students more anxious and mathematically unprepared to achieve. In college
and university, anxious math students take fewer math courses and tend to feel
negative towards math. In fact, Ashcraft found that the correlation between
math anxiety and variables such as confidence and motivation are strongly
negative. Students who are highly anxious toward mathematics tend to avoid
mathematics and take fewer math courses throughout their educational career
(Ashcraft, 2002).
According to Schar, M.H., and Kirk, E. P. (2001), because math anxiety can
cause math avoidance, an empirical dilemma arises. For instance, when a
highly math-anxious student performs disappointingly on a math question, it
could be due to math anxiety, or the lack of competency in math because of
math avoidance. Ashcraft determined that by administering test that becomes
increasingly more mathematically challenging, he noticed that even highly
math-anxious individuals do well on the first portion of the test measuring
performance. However, on the later and more difficult portion of the test,
there was a stronger negative relationship between accuracy and math anxiety.

11
An additional form of mathematics anxiety is fear. Fear, as defined by
Wigfield and Meece (2000), is the emotionality component of anxiety.
Wigfield and Meece (2000) further state that along with the feelings of fear,
comes the feeling of nervousness, tension, and unpleasant physiological
reactions to testing situations (Wigfield & Meece, 2000). Focusing on fear and
the number of other variables associated with mathematics anxiety, a
Brazilian study conducted by Utsumi and Mendes (2000) are in agreement
with many other studies that, “Anxiety present on learning situations can
generate an unfavorable attitude, which could result in an impediment to
learning” (p. 238). Karen Norwood (2004) has does extensive research on
instructional approaches and the effects on anxiety toward mathematics. She
claims that mathematics anxiety does not appear to have a particular cause. It
is seen often as the result of different factors, such as inability to handle
frustration, poor self-concept, parents and teachers attitudes toward
mathematics, and emphasis on learning through drill without understanding
(Norwood, 2000). Continuing the idea that mathematics anxiety is the result
of various factors including teachers and parents espoused the idea that once
anxiety is formed it is difficult to change. “Although attitudes may deepen or
change throughout school, generally, once formed, negative attitudes and
anxiety are difficult to change and may persist into adult life, with far reaching
consequences (p. 53). Conventional wisdom and research suggest that
students with negative attitudes toward mathematics have performance
problems simply because of anxiety (Tapia & Marsh, 2004). The emerging
theme in many studies is that mathematics anxiety has presence in students’
attitudes and the ramifications can be paramount when associated with one’s
academic career.

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Efficacy in Mathematics
In Townsend and Wilton’s (2003) research on evaluating change in attitudes
towards mathematics, they emphasize that elements of self-efficacy are
present in recent calls by educators to address the problems posed by negative
attitudes towards mathematics. As Seifert (2004) states in his report on
Understanding Student Motivation, the self-efficacy theory refers to a
person’s judgment about his/her capability to perform a task at a specific level
of performance. This belief is formed by a history of experiences that
persuade a person that he or she has what it takes to be successful in
mathematics (Townsend & Wilton, 2003). In addition, Seifert (2004) states
that the worth of the individual is connected to his or her ability to do
something well.
Jackson and Leffingwell (2000) found that there were three distinct age
groups in which the anxiety-producing problems became evident: Grades 3
and 4, grades 9-11, and college level, predominantly in freshman year.
According to their research, students became traumatized as early as
kindergarten and 16% of students experienced their first traumatic encounter
in grades 3 or 4. In her article entitled Teaching Math Their Way, states that
research has shown that fourth grade is often when students first experience
math anxiety. Encounters such as these leave little room for the development
of a student’s self-concept within the area of mathematics.
Reyes, identified self-concept as the perceptions of personal ability to learn
and perform tasks in mathematics. Students who are not confident perceive
themselves incapable and may avoid tasks that are seen as challenging or
difficult. As a result, students lack confidence in their ability to perform
mathematics, thus creating mathematical anxiety (Seifert, 2004). Raising the

13
point that students who are not confident in their skills have a lower
mathematics self-concept than those who are confident.
A student’s perception on success in mathematics has been researched for
years and many have found a direct relationship between a student’s self-
efficacy and mathematics anxiety. Mathematics anxiety has fostered such
strong research into its origin and effects on student performance. Research
has concluded that mathematics anxiety can lower a students’ performance on
subject specific tests such as mathematics.
Townsend and Wilton (2003) stated that, attitudes toward mathematics appear
more polarized than for any other curriculum area. They explain that certain
instructional strategies may be able to increase a student’s perception of their
ability to learn and therefore reduce the tension associated with mathematical
tasks. With mathematics anxiety being a contributing factor to students’
dislike, fear, and poor performance in mathematics, it is important to look into
instructional strategies to enhance and encourage learning taking place within
mathematics classrooms.
Student attitudes to mathematics
Student attitudes and performance in mathematics have varied. A number of
students enjoy mathematics, yet many others espouse negative attitudes (Ma,
2000). Extensive research supports the idea that many students suffer from
anxiety toward mathematics (Ashcraft, 2002; Stuart, 2000; and Townsend &
Wilton, 2003). Mathematics anxiety has been defined as feelings of fear,

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tension, dread, apprehension, or general discomfort that interferes with
mathematics performance (Ashcraft, 2002).
According to the National Council of Teachers of Mathematics (2000),
students should learn to value mathematics and become confident in their
ability to do mathematics. However, mathematics anxiety has stood in the way
of students becoming comfortable with their ability to perform
mathematically. Anxiety towards mathematics does not appear to have a
single cause. It is the result of various factors including parents’ and teachers’
attitudes towards mathematics, poor self-concept, and emphasis on learning
mathematics through drill without understanding (Norwood, 2000).
In my review of the literature on students’ mathematics anxiety and attitudes
and the use of hands-on instructional strategies, enhanced with technology, in
the teaching of mathematics, pertinent themes emerged. These themes
included mathematics instruction, student’s mathematics anxiety, as it relates
attitudes, and their self-efficacy. This action research will focus on the
integration of hands-on instructional practices enhanced with technology into
mathematics and the effects it has on students’ mathematics attitudes and
mathematics performance. The following summary of the literature reviews
the key factors involved with mathematics instruction, students’ self-efficacy
and the profound influence it has on students’ mathematics attitude and
performance.
Technology
Due to technology, the many facets of mathematics that were once discrete
take on new importance in the contemporary mathematics classroom (NCTM,
2004). Guha and Leonard (2002) advocate technology as a hands-on approach
to learning. Computers help to extend mathematical ideas and in turn help to

15
expand the minds of students (p. 42). Guha and Leonard (2002) maintain the
idea that computers in the elementary mathematics classroom engage students
in mathematics for longer periods and have the capability to change their
attitude and performance in mathematics. According to the NCTM (2000)
Principles and Standards for School Mathematics, technology is essential in
teaching and learning mathematics; it influences the mathematics that is
taught, enhancing a students’ learning.
In a study supporting the use of technology in the teaching and learning of
middle grades mathematics, Guerrero, Walker and Dugdale (2004) state:
“The past two decades have seen dramatic growth in the use of
technology in mathematics classrooms, diverse and appealing
explorations of potential roles for that technology, and sometimes
intense debates about the pros and cons of technology in teaching and
learning” (p. 6).
Kersaint, Horton, Stohl, and Garofalo (2003) avow that the pervasiveness of
technology in society has highlighted the need for schools to prepare students
to take advantage of emergent technology tools. Barron, Kemker, Harmes, and
Kaladjian (2003) assert that technological innovation is accelerating and
weaving its way into our society, and that it is essential for students’ to
enhance such skills as problem solving, communicating and synthesizing
information via technology. The International Society for Technology in
Education (ISTE) published their National Educational Technology Standards
(NETS) for students claiming that the intent of technology to be an integral
component or tool for learning within the context of academic subject areas.
Contemporaneous with standards movement, technology is viewed as a “tool
to communicate, conductresearch, and solve problems” (Barron, et al 2003, p.
490).

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States are taking the initiative to create technology benchmarks at each grade
level and within all curriculum areas. According to the NCTM (2005),
electronic technologies—calculators and computers—are essential tools for
teaching, learning, and doing mathematics. NCTM (2005) further states that
technology enriches the range and quality of investigations by providing a
means of viewing mathematical ideas from multiple perspectives.
Many factors influence a teacher’s choice of instructional styles in their
classroom. With technology being one of the most contentious and largely
discussed topics, does technology have a place in the classroom and in the
instruction of mathematics? Ross, Hogaboam-Gray, McDougall, and Bruce
(2002) claim that research on technology use in mathematics teaching has
focused on the contribution of technology to student learning. In a recent
study entitled Technology in Support of Middle Grade Mathematics: What
Have We Learned? Guerrero, et al. (2004) found that when technology was
used well in the middle grades, it had positive effects on student’s attitudes
towards mathematics. Further, technology use can have a positive impact on
students learning, with significant gains in mathematical achievement and
conceptual understanding (Guerrero, et al., 2004). With technology being
looked on as a key component in affecting students’ attitude and performance,
are educators properly trained to utilize such an instructional resource?
In a study focusing on mathematics education reform and technology, Ross, et
al., (2002) assert that the impact of technology might be weaker with teachers
who preferred a traditional approach to mathematics teaching and were less
technologically literate. Teacher training is an imperative component of the
integration of technology. Teachers, who are trained, feel more comfortable
integrating technology into mathematics lessons and other subject areas.
Fredrick Bennett (2002) asserts that if schools could train teachers, the

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argument goes; technology would finally deliver benefits to education.
Teacher training is a crucial component for the successful integration of
technology in the classroom. Along with training teachers to use important
instructional resources such as technology, student learning is the motivation
of such integration. In agreement, Ross, et al., (2002) emphasize that
technology enables teachers to implement their constructivist beliefs by
relieving the students of the tedium of calculation and providing them with
visual representations to support dialogue about mathematical ideas.
Technology and manipulative are being viewed as the focus of a student-
centered, non-threatening mathematics classroom that provides learners with a
diverse approach to learning. Teachers’ choice of activities and mathematics
problems can have a strong impact on the value that are portrayed in the
classroom and on how students view mathematics and its usefulness (Wilkins
& Ma, 2003). The aforementioned research supports that idea that both,
technology and hands-on instructional strategies provide students with a rich
environment in which they can explore, create, and justify answers.
Student experience in mathematics anxiety and efficacy
A number of scholars have attempted to define math anxiety. Duffy and
Furner (2002) viewed it as the emotional and mental distress that occurs in
some students while attempting to understand mathematics. Tsanwani (2009)
also views mathematics anxiety as an irrational and impedimental dread of
mathematics. Hlalele (2012) coined mathematics anxiety as a term used to
describe the panic, helplessness, mental paralysis and disorganisation that
arise among some individuals when they are required to solve a problem of a
mathematical nature. Literature further indicates that mathematics anxiety
refers to a person’s feelings of tension and anxiety that interfere with the

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manipulation of numbers and the solving of mathematical problems in a wide
variety of ordinary and academic settings (Khatoon & Mahmood, 2010;
Leppavirta,2011; Newstead, 2006; Perry, 2004). Therefore this study viewed
the term mathematics anxiety as some form of discomfort observed while
working on mathematical problems, which is usually associated with fear and
nervousness to engage in specific mathematics related situations. Geist(2010),
a proponent of new teaching methods that take student thinking into account,
also recognizes that gender issues and parental education can play a part in
math anxiety. However, he emphasizes the prominent role that teachers play
in creating concussive learning atmospheres and setting realistic targets for
their students. He noted that high risk tests that value rote learning and
memorization are the main sources of math anxiety. From a contrary view,
Lyons (2012) reported that anxiety is a fairly insubstantial obstacle. Therefore,
it makes one to question why it appears to have a crippling effect on some
students’ ability to do mathematics. This gives a neutral explanation of why
some students avoid mathematics-related subjects. It is commonly known that
anxiety will influence a student’s decisions about what classes to take, often
leading to avoidance of math (Maloney, 2012). There is also some lack of
agreement about the causes of mathematics anxiety in students. According to
Traxler
E-ISSN 2039-2117
ISSN 2039-9340
Mediterranean Journal of Social Sciences
MCSER Publishing, Rome-Italy
Vol 5 No 1
January 2014
(2013), it appears that there are three primary causes of math anxiety. These
are beliefs, learning environment, and an anticipatory response. These three

19
variables are intertwined and strengthen one another. Beliefs might include
negative stereotypes about one’s gender or race. Tobias (1993) views cultural
belief as a primary cause for female students’ mathematics troubles. This
describes the conviction that females are less proficient at mathematics. For
female students who fail, they are likely to attribute that to their natural
disposition. Cognitive restructuring of beliefs could be a partial solution to
that problem. Mitt (2012) submits a set of environmental factors that female
students are exposed to which may influence their heightened anxiety. The
other suggested causes include teacher anxiety, innate characteristics of
mathematics, failure and the influence of early-school experiences of
mathematics (Newstead, 2000). Exposure to some teaching and learning
strategies that rely on behaviourist models such as rote-memorization of rules
and the manipulation of symbols with little or no understanding instead of an
integrated conceptual structure can result in affective stumbling blocks for
students (Skemp, 2000). Teachers can also create anxiety by placing too much
emphasis on memorizing formulae, learning mathematics through drill and
practice (Greenwood, 2000). Students who experience mathematics anxiety
are more likely to delay completion or not do tasks assigned to them at all
(Owens and Newbegin, 2000). As an irrational fear towards mathematical
operations in mathematics classes, mathematics anxiety is found to hinder
learners’ positive thinking about mathematics learning and feeling calm. This
fear causes low self-esteem, disappointment and academic failure (Gresham,
2004; Akin & Kurbanoglu, 2011). In this study, the researchers focused on
aspects of mathematical anxiety such as students’ uneasiness behaviour when
doing mathematics, a failure to complete tasks on time and lack of confidence
when handling mathematics tasks. Iossi (2007) identified strategies for
minimizing anxiety which include:

20
(a) curricular strategies, such as retesting, self-paced learning, distance
education, single-sex classes, and math anxiety courses,
(b) instructional strategies, such as manipulatives, technology, self-regulation
techniques, and communication, and
(c) non-instructional strategies, such as relaxation therapy and psychological
treatment. Alternative instructional formats such as problem solving, co-
operative learning and process-oriented have been suggested in order to
prevent or limit mathematics anxiety (von Glasersfeld, 1991; Vacc, 1993 and
Greenwood (1984).
Reform efforts in the teaching of mathematics have been under way to replace
the behaviourist paradigm with methods based on constructivist models of
learning such as problem-based learning, inquiry-based learning and guided
discovery learning.
Depending on the individual and the task, a moderate amount of anxiety may
thus actually facilitate performance (Newstead, 2009). Anxiety at relatively
low to moderate levels can be constructive. Beyond a certain point, however,
anxiety becomes counterproductive in terms of performance, particularly in
the case of higher mental activities and conceptual processes. However most
studies found that most students’ anxiety levels in their studies ranges from
moderate to high (Posamentier, Smith & Stepelman, 2013).Such high levels of
mathematics anxiety cause a lot discomfort for many mathematics students
and teachers and student lecturers should strive to strike a balance between
high subject cognitive demands and high student anxiety levels. Awanta
(2000) also lamented that relationship between anxiety and learning of
mathematics is complex. He noted that anxiety as a form of arousal of
alertness can be helpful in learning but too much anxiety, particularly when
combined with perceived lack of ability can hinder learning.

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Manipulative methods (solving mathematic efficacy and anxiety)
Classrooms have long come from an era of teaching where teachers would
expect that all students did with their hands is fold them (DeGeorge, 2004).
Traditionally teachers have relied on workbooks, drills, and memorization to
present mathematical concepts (Moch, 2001). Presently teachers are exploring
the use of manipulatives in the teaching of mathematics, which have been
used for some time. Pestalozzi advocated the use of manipulative materials in
the early 1900’s and manipulatives made their way into the classroom by the
mid-1960’s (Sowell, 2000). Researchers have said that children learn better if
the mathematics instruction moves from concrete to abstract (Clements, 2000;
DeGeorge, 2004; Moch, 2001; and Sowell, 2000). Studies on the use of
manipulatives in the classroom have shown that students who are using them
outperform those who do not (Sowell, 2000).
In an article on manipulatives in mathematics, DeGeorge (2004) found that
hands-on learning helps students to more readily understand concepts and
boost their self-efficacy. In a meta-analysis comparing studies on
manipulative material in mathematics instruction, Evelyn Sowell (2000) found
that consistent use of manipulatives over a year’s period resulted in positive
effects in elementary grade students.
Student achievement in mathematics has been an area of study for several
years and researchers are linking the use of manipulatives to greater student
achievement. In Sinan Olkun’s (2003) study comparing computer-generated
manipulatives with concrete manipulatives, results showed positive effects on
student’s geometric reasoning. Olkun’s research shows that fourth grade
students gained more knowledge with the use of concrete manipulatives. In an

22
action research study entitled Manipulatives Work!, Peggy Moch (2001)
found that when she utilized manipulatives within her mathematics instruction
the posttest results for percentage of correct answers increased from 49
percent to 59 percent.
Alternative data were analyzed to further support her notion that manipulative
use in the classroom is effective. Students demonstrated an increase in Florida
Comprehensive Assessment Test (FCAT) practice tests of 4.47-13.97 percent.
Moch (2003) affirms that students’ general reaction to the use of the
manipulatives was encouraging as the students experienced moments of
understanding while learning. Hands-on strategies such as manipulatives have
been widely used in the classroom and are strongly related to student
achievement (Olkun, 2003). Sowell’s (2000) meta-analysis on manipulative
materials in mathematics instruction disproved older theories that
manipulative were ineffective and proved that mathematical manipulative
produced greater achievement than not using them in elementary school.
With the current pressure of standardized testing and diverse classrooms,
establishing and maintaining environments where students are eager and
motivated to learn continues to be a goal of the mathematics education
community (Guhu & Leonard, 2002). Along with researching the outcomes of
achievement related to the integration of hands on strategies such as
manipulative, recent studies have looked into the roles that are taken by
teachers and students when manipulatives are used in the classroom.
In Moyer and Jones’ (2004) research on the roles of the teacher, student, and
manipulatives in the mathematics classroom, they bring to light the awareness
of the interactions between teachers and students in the mathematics
classroom. Teachers’ roles are critical in negotiating and establishing the

23
quality of classroom interactions (Moyer & Jones, 2004). Student’s
construction of knowledge is based on their interactions and selection of
mathematical tools (Moyer & Jones, 2004). Teachers play a very strong role
in the selection and control of the mathematical tools that are used in the
classroom. Moyer and Jones (2004) agree that the teacher’s role is very
important. However, sharing the choice is essential in establishing some
control on the part of the student and their choice of manipulative, which leads
to the construction of mathematical knowledge.
Moyer and Jones (2004) advocate the use of manipulatives within
mathematics instruction and the availability of those manipulatives at the
student’s desks during instruction. They feel that the availability of
manipulatives will give the students the opportunity to devise their own
solution strategies and promote autonomous thinking and confidence in
learning mathematics.

24
CHAPTER THREE
RESEARCH METHODOLOGY
This study aimed at examining the impact mathematics efficacy and anxiety
on student performance in introductory technology in Lagos State.
This chapter dealt with methods and procedures that were used in the study.
These are discussed under the following sub-headings:
a. Research design
b. Population of the study
c. Sample and sampling technique
d. Research instrument
e. Validity and reliability of the instrument
f. Procedure for data collection
g. Procedure for data analysis
Research Design
The study adopted survey research method. This is because the researcher is
only interested in determining the influence of the independent variable
without manipulating any of the variables
Population of the study
The population for this study consisted of selected teachers in all public
secondary schools in Lagos State
Sample and sampling technique
A simple random sampling was employed in selecting one hundred and fifty
(150) teachers from ten (10) public secondary schools in Lagos State. Fifteen
teachers were randomly selected from each school using fish bowl method
without replacement.

25
Instrumentation
The instrument used for data collection in this study is Students’ Performance
Questionnaire (SPQ). The questionnaire was designed to be simple, easy to
understand, unambiguous and contain the appropriate questions that were able
to influence the collection of the designed data for the study
The questionnaires are of two sections A and B. Section A sought personal
data from the teachers on their age, rank, qualifications, schools and years of
experience. Section B has twenty (20) items that sought teachers’ opinion on
the variable selected for the study
The modified like four points scale with options ranging from strongly agree
to strongly disagreed was adopted while designing the instrument.
Validity of the Instrument
The questionnaires were constructed and presented to the project supervisor
and two other lecturers in the department for the validation
Reliability of the Instrument
Test-retest method was adopted to determine the reliability of the instrument.
Ten copies of the instruments were administered twice in Ogun State at two
weeks interval. Pearson Product Moment Correlation (PPMC) was employed
to determine the correlation co-efficient. The co-efficient of reliability was
found to be 0.02 which means the instrument was found useful and consistent
for which of it was prepared.

26
Procedure for Data Collection
The researcher administered the questionnaires personally in each of the
schools to the teachers that formed part of the study.
Explanations were made where necessary for clarifications on questionnaires.
Efforts were made to collect the questionnaires on the same day so as to
ensure high returns. Out of the one hundred and fifty (150) copies
administered, ten (10) copies representing 6.7% could not be used, while the
remaining two hundred and forty (140) copies that were usable were finally
coded and subjected to analysis
Procedure for data analysis
The data collected were coded and subsequently subjected to descriptive
statistics of frequency counts and percentage for demographic information
which inferential statistics of chi square(x2) was used to test hypothesis at 0.05
level of significant.

27
CHAPTER FOUR
DATA PRESNTATION, ANALYSIS AND DISCUSSION OF
FINDINGS
This study was carried out to find out the relationship between
mathematics efficacy, anxiety and students’ performance in introductory
technology in Alimosho Local Government. This chapter deals with the
analysis of data obtained, testing of hypotheses postulated to guide the
study and discussion of findings. The results are presented in tables for
easy understanding.
RESULTS
Table 1: Distribution of questionnaires by school
S/NO NAME OF
SCHOOL
NO
ADMINISTERED
NO
RETURNED
%
1 Oke – Odo High
School
15 14 9.33
2 Alimosho
Grammar School
15 15 10.0
3 State High
School
15 13 8.67
4 Community High
School
15 14 9.33
5 Ikotun High
School
15 15 10.0
6 Muslim College,
Egbe
15 14 9.33
7 Tomia College,
Agbado
15 12 8.00
8 Lagos Model
College
15 15 10.0
9 Sanmori Junior
High School
15 13 8.67
10 Command
Secondary
School
15 15 10.0
Total 150 140 93.3

28
From the table, it could be observed that a total of 15 copies of the
questionnaire were administered at Oke – Odo High School while 14
were returned representing 9.33 percent. 15 questionnaires were
administered and returned by Alimosho Grammar School representing 10
percent. A total of 15 questionnaires were administered to State High
School and 13 were returned representing 8.67percent. 15 questionnaires
were administered to Community Junior Grammar School and 14 were
returned, representing 9.33 percent of the sample. A total of 15
questionnaires were administered and returned at Ikotun High School
representing 10 percent, 15 questionnaires to Muslim College and 14
were returned representing 9.33 percent of the sample.
In Tomia Junior Secondary School, a total of 15 questionnaires were
administered and 12 were returned representing 8.00 percent while 15
were administered at Lagos Model College and 13 were equally returned
representing 8.67 percent while 15 were administered and returned in
Command Secondary School representing 10 percent of the sample.
Table 2: Age of Respondents
Age Frequency Percentage
20 – 30 years 42 30%
31 – 40 years 77 55%
41 – 50 years 21 15%
51 year and above - -
Total 140 100%
From the table, it could be observed that a total of 42 respondents which
represents 30% falls between the age of 20 – 30 years, 77 which
represents 55% falls between age of 31 – 40 years and 21which
represents 15% falls between the age of 41 – 50 years.
Table 3: MaritalStatus of Respondents
Status Frequency Percentage
Married 105 75%
Not Married 35 25%
Divorced - -
Total 140 100%

29
Table 3 shows that a total of 105 respondents representing 75% were
married. 35 of them were not married representing 25%.
Table 4: Genderof Respondents
Sex Frequency Percentage
Male 56 40%
Female 84 60%
Total 140 100%
From the table it could be observed that a total of 56 respondents were
males representing 40% while 84 of them were females representing 60%
of the sample.
Table 5: Qualificationof Respondents
Qualification Frequency Percentage
TC11 3.5 2.5
NCE 70 50.0
First Degree 66.5 47.5
Master Degree - -
Above Master
Degree
- -
Total 140 100%
Table 5 shows the distribution of questionnaire by respondent
qualification. A total of 3.5 respondents were TC11 holders representing
2.5%. 70 of them were NCE holders representing 50% while a total of
66.5 respondents were first degree holders representing 47.5%.
Table 6: Rank of Respondents
Rank Frequency Percentage
Subject Teacher 112 80%
H.O.D 14 10%
V. Principal 10.5 7.5%
Principal 3.5 2.5%
Total 140 100%
Table 6 shows that a total of 112 respondents were subject teachers
representing 80%, 14 were H.O.D, representing 10% of the sample, 10.5
were Vice Principal which represents 7.5% while 3.5 were Principals
representing 2.5% of the sample.

30
Table 7: Teaching Experience ofRespondents
As shown in table7, 105 respondents representing 75% had teaching
experience of 0-10 years, while 21 representing 15% had 11-20 years’
experience. 14 which represent 10% of the sample had 21-30years
teaching experience.
TESTING OF HYPOTHESES AND DISCUSSION OF FINDINGS
This section deals with testing the various hypotheses formulated for the
study. The analyses were presented in tables and discussions made below.
Chi-Square statistical tool was used to test the hypotheses which were
either accepted or rejected at 0.05 level of significance. The analyses are
presented in tables 8,9, 10, 11 and 12 below:
Hypothesis 1: There is no significant relationship between students’ age
and their academic performance on mathematics in introductory
technology.
Table 9: Chi-Square analysis relationship of students’ age and their
academic performance on mathematics in introductory technology.
Response Total Percentage (X2)Cal X2
Table
value
D.F LS Remark
SA 287 30.34
A 340 35.94
D 259 27.38 78.45 16.92 9 0.05 Significant
SD 60 6.34
Total 946 100
X2Cal = 78.45, X2 table= 16.92, df= 9 at 0.05
Experience Frequency Percentage
0-10 years 105 75
11-20 years 21 15
21-30 years 14 10
31-40 years - -
41 years and above - -
Total 140 100

31
The calculated Chi-Square (X2) of 78.45 was greater than Chi-Square
(X2table value of 16.92 with df= 9 at 0.05 level of significant. Therefore,
the state a hypothesis is here by rejected, this implies that there is
significant relationship between parents occupation and students
performance of students in Alimosho Local Government of Lagos State.
This finding is line with Gibson and Dembo (2000) that students who are
mature perform better in introductory technology and mathematics. Due
to their maturity and their seriousness in their studies and their academic
performance. The finding is also supported by Kelly (2000) who said that
mature students are not so much affected by anxiety in their performance
in introductory technology and other science related courses. Brown
(2009) argued that anxiety has no effect on students’ performance in
introductory technology; he claims that students decline performance in
introductory technology is only caused by non-challant of students.
Hypothesis 2: There is no significant relationship between students’
attitude and academic performance on mathematics in introductory
technology in Alimosho Local Government.
Table 9: Chi-Square (X2
) analysis on relationship between students’
attitude and academic performance on mathematics in introductory
technology.
Response Total Percentage (X2)
Cal
X2Table
value
D.F LS Remark
SA 328 34.42
A 307 32.21
D 193 20.25 386.91 16.92 9 0.05 Significant
SD 125 13.12
Total 953 100
X2Cal= 386.91, X2Tab= 16.92, D.F=9 at 0.05
The table revealed that for 953 responses, strongly agreed was
328(34.42%). Agreed was 307 (32.21%). Disagreed was 193(20.25%)
while strongly disagreed was 125 (13.12%). The calculated Chi-Square
(X2) of 386.91 was greater than table value of 16.92 with df=9 at 0.05
level of significant.

32
Therefore, the stated hypothesis is here by rejected, indicating that there
is significant relationship between students’ attitude and their academic
performance in introductory technology in Alimosho Local Government
of Lagos State. This finding is in line with Ashcraft and Moore (2009)
who said that the students’ attitude will always reflect in how they
perform in introductory technology and other science subjects. The
finding also supported Zeidner and Mathew (2011) who reported that the
involvement of students in bad attitudes like laziness, truancy, non-
challant behaviour affect their performance in introductory technology.
Alsup’s (2004) believed that student attitude has no significant influence
on their performance in science subjects. The respondents agreed that
students’ attitudes have effect on the students’ performance in
introductory technology. Therefore, the researcher submitted that
students’ attitudes like laziness, bullying, truancy influence the students’
performance in introductory technology. The hypothesis is rejected. It is
concluded that there is significant relationship between students’ attitude
and their performance in introductory technology.
Hypothesis 3: There is no significance relationship between student
grade level and academic performance on mathematics in introductory
technology.
Table 10: Chi-Square analysis on relationship of students’ grade level
and academic performance on mathematics in introductory
technology.
Response No. of
Response
Percentage X2
Calculation
X2Table
value
D.F LS Remark
SA 320 33.72
A 380 40.04
D 225 23.71 104.2 16.92 9 0.05 Significant
SD 24 2.53
Total 949 100
X2Cal=104.2, X2Table= 16.92, df= 9 at 0.05.
The calculated chi-square (X2) of 104.2 was greater than the Chi-Square
(X2) table value of 16.92, with df=9 at 0.05 level of significance.

33
Therefore, the stated hypothesis is hence by rejected; this implies that
there is significant relationship between students’ grade level and
academic performance in introductory technology in Alimosho Local
Government. The finding is in line with Kyttala and Bjorn (2010) who
opined that students’ grade level has elastic effects on their academic
performance in introductory technology.
Mark (2002) also supported that students’ grade level may affect
students’ performance in introductory technology.
Schar and Kirk (2001) stated that one of the greatest factors that affect
student’s attendance is the students’ grade level which may lead to poor
performance in basic science subjects while Utsumi and Mende (2000)
reported that students’ grade level have no effect on the performance of
the students on mathematics in introductory technology. The Chi-Square
analysis shows that there is significant relationship between students’
grade level and academic performance in introductory technology.
Therefore, the researcher submitted that grade level of students influence
their and academic performance on mathematics in introductory
technology and other science subjects. The hypothesis is here by rejected
and it is concluded that there is significant relationship between students’
grade level and academic performance on mathematics in introductory
technology.
Hypothesis 4: There is no significance relationship between students’
gender and academic performance on mathematics in introductory
Table 11: Chi-Square analysis on the relationship of students' gender and
academic performance on mathematics in introductory technology in
Alimosho Local Government.
Response
s
No. of
Response
s
Percentag
e
X2Ca
l
X2Tabl
e value
D.
F
LS Remark
SA 290 30.63
A 340 35.90
D 267 28.19 78.32 16.92 9 0.0
5
Significa
nt

34
SD 50 5.28
Total 947 100
The calculated Chi-Square (X2) of 78.32 was greater than the Chi-Square
(X2) table value of 16.92, with df= 9, at 0.05 level of significant.
Therefore, the stated hypothesis is here by rejected, this implies that there
is significant relationship between students gender and academic
performance in introductory technology in Alimosho Local Government.
This finding is in line with Townsend and Wilton (2003) who reported
that gender has serious effect on students academic performance in
introductory technology of students in schools. Tapia and Marsh (2004)
also agreed that students’ academic performance on mathematics in
introductory technology is being affected by students’ gender. Seifert
(2004) indicate that students gender have no influence on student’s
performance and academic achievements in introductory technology.
Hypothesis 4 shows that there is significant relationship between gender
of students and students’ academic performance on mathematics in
introductory technology. The researchers opined that students gender
have significant influence on academic achievements in introductory
technology. The hypothesis is here by rejected. It is then concluded that
there is significant relationship between students’ gender and their
academic achievements on mathematics in introductory technology.
Discussion of the finding
It can be recalled that the purpose of this study was to explore the
mathematics anxiety levels, efficacy of mathematics students in
introductory technology and to examine the effect of demographic
factors, which are gender, age, attitude and grade level. It was also

35
hypothesized highly that males experience math anxiety less than
females.
This study found that there was a significant difference in mathematics
anxiety levels of students according to gender. Both descriptive statistics
and inferential indicated that males experience less than their female
counterparts. This finding is consistent with studies by Bidin et al.
(2003); Woodard (2004; Sahin (2008) and Karimi and Venkatesan
(2009), which determined that there was a relationship between
mathematics anxiety and gender, all of which noted significant
differences in mathematics anxiety according to gender, with female
students exhibiting higher math anxiety than their male counterparts.
However, these findings contradict the findings of Marsh (2004) and
Stevens (2013) which concluded that there is no relationship between
mathematics anxiety and gender. Long research history in this area has
shown that male advantage in mathematics achievement is a universal
phenomenon (Mullis et al., 2000). Kaufman (2006) recognized that math
interests of males are better than the females from secondary school
onwards.
This study found that there was a significant difference in mathematics
anxiety levels of students according to age. Descriptive statistics
indicated that 16-20 year old students experience more math anxiety than
their older students. However further inferential statistics proved it
insignificant. This is consistent with findings by Calvert (2001) and
Hokpo et al. (2003) which revealed that age was not statistically
significant in the determination of the level of math anxiety. Rambow
(2008) noted that older women experienced a significantly high level of
math anxiety. McCarthy (1986)’s findings revealed no significant
difference in math anxiety between older and younger students.

36
Gender differences in mathematics anxiety have been extensively studied
and results are inconsistent, with a number of studies revealing that
females have higher levels of mathematics anxiety than males (Alexander
& Martray, 1989) and others not confirming significant differences.
Baloglu and Kocak (2006) found that gender effects of mathematics
anxiety varied with the context. Age is another factor where contradictory
findings are reported in the literature. Hembree, (1990), did not find any
age-related differences, but Baloglu and Kocak (2006) found that older
students exhibited more total mathematics anxiety than younger ones,
particularly in mathematics testing and course situations. Craig, Brown,
and Baum (2000) had completely different views about math anxiety,
arguing that anxiety has its origins in a complex interaction of
environmental, psychological, and biological events and processes.

37
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
This study was designed to investigate the relationship between
mathematics efficacies, anxiety and students performance in introductory
technology in Alimosho Local Government of Lagos State. To find out
this, four hypothesis were formulated. A review of related literature was
carried out and this covered the following.
a. Mathematics instruction
b. Mathematics anxiety
c. Efficacy in mathematics
d. Student attitudes to mathematics
e. Manipulative methods (solving mathematic efficacy and anxiety)
f. Technology
g. Student experience in mathematics anxiety and efficacy
For the purpose of this study, the survey method was applied which is a
form of survey research design.
A total of one hundred and fifty questionnaires were distributed while one
hundred and forty were returned. Therefore, the sample for the study
consists one hundred and forty were selected from the population. A self-
developed questionnaire designed in line with likes four points’ scales
was used for data collection.
The questionnaire has two sections A and B. Section A focused on
demographic data while section B focused on variables selected for the
study. The questionnaire was validated and subjected to test-retest
method.
Data collected were subjected to Pearson Product Moment Correlation
(PPMC) which yielded 0.72. The validated questionnaires were
administered with the help of research assistant to the respondents. Data

38
collected were analyzed using the frequency counts and simple
percentage for demographic data while inferential statistical of Chi-
Square (X2) were used to test the five hypotheses at 0.05 level of
significance. Results were presented in tables and figures and were
discussed.
Based on the findings from the study, it could be concluded that there was
relationship between mathematics efficacy, anxiety and students’
performance and other science related courses.
Educational Implication of the findings
The results of this study have multiple implications for the assessment of
college students’ mathematics self-efficacy and mathematics anxiety.
Some of these implications relate to course structure, and others relate to
computerized assessment of learning.
Course structure. When exploring students’ self-efficacy and anxiety
regarding their college mathematics courses, it is important to consider
how the course is structured, including how students are assessed and the
resources available to the students. It is likely that students will feel more
or less anxious about certain aspects of their mathematics courses,
depending on how those aspects affect their grades. For example, the
students in the present study typically seemed anxious about every exam
in their mathematics course because the results would have a significant
impact on their grade. The students were not, however, very anxious
about their homework assignments because they believed they would
always be able to get a good grade on the assignments. Furthermore, the
students were not very anxious about their assignments, because they
believed that they were provided with sufficient resources to complete all
of the assignments. The students’ mathematics self-efficacy and

39
mathematics anxiety can be influenced by how the course is organized,
and it is important for instruments exploring these constructs to take into
account the structure of the students’ current mathematics courses in
order to cover all of the important areas where the students might feel
anxious.
Computerized assessment. Researchers need to consider how the
assessment is administered in mathematics courses when designing
mathematics self-efficacy or mathematics anxiety instruments. When the
students discussed in interviews their anxiety regarding their mathematics
exams, most commented on their dislike of taking the tests on acomputer,
which was a requirement in the precalculus course. I definitely get
nervous because it’s on the computer because you know when you click
that button, even though I know that it’s going to be right, I second guess
myself so much. I don’t want to click that button and see that it’s wrong.
There’s no way to double-check your answer.
Researchers have found that students with higher levels of mathematics
anxiety are likely to perform better on paper-and-pencil tests than on
computerized tests (Ashcraft, 2002). Although the exact reason for the
difference between performances on computerized and paper tests is not
fully understood, a number of explanations have been given as to why
students might not perform as well on computerized tests: These
explanations involve computer anxiety, familiarity with computers,
screen size and resolution, test flexibility, and cognitive processing
(Leeson, 2006).
Another possible reason for a performance difference on computer and
paper mathematics tests is that students usually cannot receive partial
credit for any correct mathematical work they have done when using a

40
computer; instead, all of the emphasis is placed on whether or not the
answer is correct. The students commented on how this feature made
them anxious about taking the tests online, with one student explaining
“Especially since the tests are online, because I’m used to…if I miss a
negative, well the teacher will see that I had everything else right and I’ll
get partial credit.” The lack of partial credit on the exams put pressure on
the students, emphasizing that they could not make any trivial
mathematical errors such as entering numbers into a calculator incorrectly
or forgetting a negative sign. The formatting and presentation of the
exams on the computer also might have influenced the anxiety the
students felt toward the exams. Many of the students commented that
immediate responses from the computer decreased their confidence
during the exam. One student expressed this by saying, “The thing I don’t
like is that it tells you right then if you got it right. That can be nice when
you were right, but it’s really stressful if you got it wrong.” Each question
that the students answered incorrectly would increase the pressure they
felt on the remaining questions. Also, based on the students’ responses in
this study, many would have benefited from the removal of a timer
display during the exam. These aspects of the assessment benefited from
the removal of a timer display during the exam. These aspects of the
assessment in the mathematics course should be taken into consideration
when exploring mathematics self efficacy and mathematics anxiety.

41
Recommendation
Based on the findings of the study, the researcher recommends as follows:
i. The students in the initial stages of the primary education should be
made familiar with science base mathematical skills so that they have
opportunities for learning mathematics
ii. Teachers should strive to understand mathematics anxiety and
implement teaching and learning strategies so that students can
overcome their anxiety.
iii. Teachers/facilitators should be positive and supportive as well as
employing teaching methods that empower students to develop
positive attitudes towards mathematics.
iv. Teachers should demonstrate interest in mathematics in order to
raise students’ motivation in mathematics as a means of helping
students to reduce their math anxiety.
v. Teaching methods which include less lectures, more students
directed classes and more discussions.
vi. Test anxiety can be minimized if addressed at an early age.
Students need to have good study skills and test taking skills.
Limitationtothe Study
This study was limited by incorporative of the respondents to fill the
questionnaire on mathematics efficacy, anxiety and students performance
in introductory technology in Alimosho Local Government and this
limitation was overcame through persuasion. The information collected
will be used for educational purpose and will be kept confidential.

42
Suggestions for the further studies
Establishing the importance of using the self-efficacy scale in conjunction
with the mathematics anxiety scale also needs to be investigated. The
concept of mathematics anxiety and the relationship with mathematics
performance can also be investigated in other groups of students,
including children, adolescents and older adults. The concept of self-
efficacy for mathematics needs to be investigated further to test the
relationship strength with larger samples and in other situations to
validate the instrument. The self-efficacy for mathematics tool developed
by Andrew et al. (2009) needs further evaluation of the two-factor format
because this study found a small correlation with the factor of arithmetic
concept.
More research is needed to show teachers how they can help student
combat anxiety every day in the classroom. By working closely with
parents, teachers can assure that parents understand the effects of test
preparation on academic achievement and levels of anxiety. Reducing
anxiety levels in students is important for helping to increase academic
achievement.
A study focusing on how anxiety affects younger students would have to
involve observations from parents and teachers. Self-report measures
would need to be appropriate for the age of the students. Another problem
with elementary students is a lack of self-awareness. Young children do
not always know how to explain what they are feeling and why.
Questionnaires for parents and teachers would need to be developed as
well. It would be interesting to learn about the effects of resource room
education on anxiety for different age groups. Students might be more

43
sensitive about be spending time apart from their general education peers
at different ages.
Conclusion
In this study, the views of teachers were sought on the impact of
mathematics efficacy, anxiety and students performance in introductory
The findings of this study showed that
o Student age have an impact on academic performance of students
on mathematics in introductory technology in Alimosho Local
Government.
o Student attitudes have an impact on academic performance of
students on mathematics in introductory technology.
o Students’ grade levels have an impact on academic performance of
students on mathematics in introductory technology.
o Students’ genders have an impact on academic performance of
students on mathematics in introductory technology in Alimosho
Local Government.

44
APPENDIX
HYPOTHESIS 1:
SA A D SD TOTAL
105 80 40 10 235
55 74 90 19 238
36 99 80 20 235
91 87 49 11 238
287 340 259 60 946
O E O-E (O-E)2
(O-E)2
/E
105 71.30 33.7 1135.69 15.93
80 84.46 -4.46 19.89 0.24
40 63.34 -23.34 544.76 8.63
10 14.91 -4.91 24.11 1.69
55 72.21 -17.21 296.18 4.10
74 85.54 -11.54 133.17 1.56
90 65.16 24.84 617.03 9.47
19 15.10 3.9 15.21 1.01
36 71.30 -35.3 1246.09 17.48
99 84.46 14.54 211.41 2.50
80 63.34 16.66 277.56 4.38
20 14.91 9.09 82.63 1.74
91 72.21 18.79 353.06 4.89
87 85.54 1.46 2.13 0.03
49 65.16 -16.16 261.15 4.01
11 15.10 -4.10 16.81 1.11
X2
= 78.75
HYPOTHESIS 2
SA A D SD TOTAL
8 37 115 78 238
135 66 23 12 236
117 83 20 20 240
68 121 35 15 239
328 307 193 125 953

45
O E O-E (O-E)2
(0-E)2
/E
8 81.91 -73.91 5462.69 66.69
37 76.67 -39.67 1573.71 20.53
115 48.20 66.80 4462.24 92.58
78 31.22 46.71 2181.82 70.10
135 81.23 53.77 2891.12 35.59
66 76.03 -10.03 100.60 1.32
23 47.79 -24.79 614.54 12.86
12 30.95 -18.95 359.10 11.60
117 82.60 34.40 1183.36 14.33
83 77.31 5.69 32.38 0.42
20 48.60 -28.60 817.96 16.83
20 31.48 -11.48 131.79 4.19
68 82.26 -14.26 203.35 2.47
121 76.99 44.01 1936.88 25.16
35 48.40 -13.40 179.56 3.71
15 31.35 -16.35 267.32 8.53
X2
= 386.91
HYPOTHESIS 3:
SA A D SD TOTAL
116 82 33 7 238
47 85 96 7 235
100 86 45 9 240
57 127 51 3 238
320 380 225 26 951
O E O-E (O-E)2
(O-E)2
/E
116 80.08 35.92 1290.25 16.11
82 95.10 -13.10 171.61 1.80
33 56.31 -23.31 543.36 9.65
7 6.51 0.49 0.24 0.04
47 79.07 -32.07 1028.48 13.01
85 93.90 -8.90 79.21 0.84
96 55.60 40.40 1632.16 29.36

46
7 6.42 0.58 0.34 0.05
100 80.76 19.24 370.18 4.58
86 95.90 -9.90 98.01 1.02
45 56.78 -11.78 138.77 2.44
9 6.56 2.44 5.95 5.57
57 80.08 -23.08 532.69 6.65
127 95.10 31.90 1017.61 10.7
51 51.31 -0.31 0.096 0.50
3 6.51 -3.51 12.32 1.89
X2
= 104.2
HYPOTHESIS 4:
SA A D SD TOTAL
100 85 38 12 235
58 71 90 17 236
35 101 88 12 236
97 83 51 9 240
290 340 267 50 947
O E O-E (O-E)2
(O-E)2
/E
100 71.96 28.04 786.24 10.93
85 84.37 0.63 0.40 0.01
38 66.26 -28.26 798.63 12.05
12 12.41 -0.41 0.17 0.01
58 72.27 -14.27 203.63 2.82
71 84.73 -13.73 188.51 2.22
90 66.54 20.46 418.61 8.27
17 12.46 4.54 20.61 1.65
35 72.27 -37.27 1389.05 19.22
101 84.73 16.27 164.71 3.12
88 66.54 21.46 460.53 5.20
12 12.46 -0.46 0.21 0.02
97 73.50 23.50 552.25 7.51
83 86.17 -3.17 10.05 0.12
57 67.67 -16.67 277.89 4.11
9 12.67 -3.67 13.47 1.06
X2
= 78.32

47
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49
NATIONAL TEACHERS’ INSTITUTE, KADUNA
POST GRADUATE DIPLOMA IN EDUCATION
Mathematics efficacy, anxiety and students performance in introductory
technology
I am postgraduate student of the above named school. I am carrying out a
study on Mathematics efficacy, anxiety and students performance in
introductory technology.
This study is purely on academic exercise therefore; your responses will
be used mainly for academic purpose and treated with utmost
confidentiality.
Kindly fill as appropriate this questionnaire and return it to the
undersigned. Thanks for agreeing to participate in this study.
MUSTAPHA, Mukadas Adeniyi.

50
SECTION A
(1) Age of Respondents.
20-30 years ( )
31-40 years ( )
41-50 years ( )
51 years and above ( )
(2) Marital Status of Respondents
Married ( )
Not Married ( )
Divorced ( )
(3) Gender of Respondents
Male ( )
Female ( )
(4) Rank of the Respondents
Subject Teacher ( )
Head of Department ( )
Vice Principal ( )
Principal ( )
(5) Qualification of Respondents
Grade 11 ( )
N C E ( )
First Degree ( )
Master’s Degree ( )

51
Above Master’s Degree ( )
(6) Teaching Experience of Respondents
0-10 years ( )
11-20 years ( )
21-30 years ( )
31-40 years ( )
41 years and above ( )
SECTION B
In this section, you are required to tick (  ) in the option depending on which
one that represent your opinion.
Note:
SA = Strongly Agree
A = Agree
D = Disagree
SD = Strongly Disagree
S/N QUESTIONS SA A D SD
1 Students in the junior secondary schools do
perform better than those in the senior secondary
schools on mathematics in technology and other
science subjects.
2 Mature students have the tendency to perform
very well on mathematics in introductory
technology due to their experiences than those that
are not matured.
3 Young students improve faster on mathematics in
introductory technology than old students.
4 Mature students learn introductory technology
better than the young ones.

52
5 Mature students tend to perform better in
mathematics than the young ones.
6 Serious students perform better in mathematics
than those that are not serious.
7 Serious students perform better in introductory
technology than those that are not serious.
8 Students playing truancy in school score better
marks than those that are regular.
9 Students who are attentive during introductory
technology class perform woefully in the subject.
10 Students who always conduct research do
understand and perform better in the subject.
11 Students in lower grades perform better in
introductory technology than those in upper grades.
12 Students in upper grades have the same level of
achievements in introductory technology with
those in lower grades.
13 Senior students achieve better in mathematics than
the junior ones.
14 Students in upper grades perform better than those
in lower class.
15 Students both in lower and upper perform
woefully in introductory technology.
16 Female students perform better on mathematics in
introductory technology than the male students.
17 Male students are serious than female students in
introductory technology.
18 Male students have the charisma to copebetter in
introductory technology than their female friends
counterparts.
19 Female students have the opportunity of going for
further research in introductory technology than
their male counterparts.
20 Female students tend to performed better in
mathematics than male students.

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