Power supplies such as AC-DC converters rely on electronic components. These power supplies convert alternating current (AC) voltage to direct current (DC) voltage. The electronic circuit known as a “power supply unit” must perform this task reliably for a piece of electronic equipment to function correctly.

A power supply unit consists of four core components. Let’s take a look at each of them before delving into power supply component availability.

1. The Transformer
The transformer is used to step the AC voltage up and down as well as provide isolation between the electronic system and the AC power. It transfers electrical energy between the primary winding and secondary winding, and it does so without changing the frequency. The transformer’s primary winding connects to the ac voltage source, while the secondary one correlates to the load. The two windings aren’t physically connected, but there is an induced voltage in the secondary winding in accordance with Faraday’s law.

2. The Rectifier
The rectifier is responsible for changing AC power to pulsating DC power. The basic rectifier is a diode — that is, a unidirectional device operating as a rectifier in the forward direction. The half-wave, the full-wave bridge type, and the full-wave center-tapped are the three basic rectifier circuits that use diodes.

3. The Filter
The filter changes the pulsating DC produced by the rectifier to a smooth DC level. It suppresses ripple, which is the AC component in a signal following rectification. High ripples can damage the load. There are two main types of filters for power supplies: C-filters and RC-filters. C-filters are the simplest version of the two.

4. The Regulator Circuits
The voltage regulator helps ensure that the DC output voltage is steady regardless of any variation in the input voltage, which enables the load to operate properly. The most common types of regulators are the series voltage regulator and the shunt voltage regulator.

INTRODUCTION TO WELDING AND FABRICATION TECHNOLOGY

The term “metal fabrication” refers to the processes used to create a finished part or product by shaping, adding, or removing material from a raw or semi-finished metal workpiece. The following headings below provides an overview of the types of fabrication processes available, outlining what they entail, what materials they accommodate, and what applications for which they are.

Cutting
Cutting is the process of separating a metal workpiece into smaller pieces. There are several cutting methods employed, each of which offers unique characteristics that make it suitable for different applications.
The oldest method of cutting is sawing. This process utilizes cutting blades either straight or rotary to cut materials into different sizes and shapes. Automatic sawing operations allow manufacturers to achieve greater precision and accuracy in their cut parts without sacrificing processing speed.
One of the newer methods of cutting is laser cutting. This process employs the use of a high-powered laser to cut materials to the desired shape and size. Compared to other cutting processes, it offers higher cutting precision and accuracy, especially for complex and intricate part designs.
Machining
Machining is a subtractive process, meaning it creates parts and products by removing material from the workpiece. While some manufacturers continue to use manual machining technologies, many are turning to computer-controlled machining equipment, which offers tighter tolerances, greater consistency, and faster processing speed.
Two of the most common CNC machining processes are CNC milling and CNC turning. CNC milling operations rely on rotating multi-point cutting tools to remove excess metal from a workpiece. While the process is often used as a finishing procedure, it can be used to complete an entire project. CNC turning operations use single-point cutting tools to remove material from the surface of a rotating workpiece. This process is ideal for the creation of cylindrical components with precise internal and external elements.
Welding
Welding refers to the process of joining materials—typically metals such as aluminum, cast iron, steel, and stainless steel—together using high heat and pressure. There are many welding methods available—including tungsten inert gas (TIG) welding, metal inert gas (MIG) welding, shielded metal arc welding (SMAW), and flux-cored arc welding (FCAW)—all of which entail different welding materials and skill requirements. Manufacturers can employ manual or robotic welding technology depending on the size and complexity of the welding project.
Punching
Punching operations utilize specialized tooling (i.e., punch and die sets) and equipment (i.e., punch presses) to cut out sections from flat workpieces in medium to high production runs. CNC punching equipment is used for light and heavy metalworking applications.
Forming
Forming involves the shaping and reshaping of solid metal into the desired part or product. There are several different forming processes available, including bending, drawing, extrusion, forging, pulling, rolling, and stretching. They are commonly used with sheets and plates—as well as other material forms—to produce simple components to complex assemblies.
Metal fabrication encompasses a wide range of processes, including, but not limited to, cutting, machining, welding, punching, shearing, and forming.
WELDING
Welding is a fabrication process used to join materials, usually metals or
thermoplastics, together. During welding, the pieces to be joined (the workpieces) are
melted at the joining interface and usually a filler material is added to form a pool of
molten material (the weld pool) that solidifies to become a strong joint.
In contrast, Soldering and Brazing do not involve melting the workpiece but rather a
lower-melting-point material is melted between the workpieces to bond
Types of Welding
There are many different types of welding processes and in general they can be
categorized as:
Arc Welding: A welding power supply is used to create and maintain an electric arc
between an electrode and the base material to melt metals at the welding point. In
such welding processes the power supply could be AC or DC, the electrode could be
consumable or non-consumable and a filler material may or may not be added.
The most common types of arc welding are:
1. Shielded Metal Arc Welding (SMAW): A process that uses a coated
consumable electrode to lay the weld. As the electrode melts, the (flux)
coating disintegrates, giving off shielding gases that protect the weld area
from atmospheric gases and provides molten slag which covers the filler
metal as it travels from the electrode to the weld pool. Once part of the weld
pool, the slag floats to the surface and protects the weld from contamination
as it solidifies. Once hardened, the slag must be chipped away to reveal the finish weld
2. Gas Metal Arc Welding (GMAW): A process in which a continuous and
consumable wire electrode and a shielding gas (usually an argon and carbon
dioxide mixture) are fed through a welding gun.
3. Gas Tungsten Arc Welding (GTAW): A process that uses a nonconsumable
tungsten electrode to produce the weld. The weld area is protected from
atmospheric contamination by a shielding gas, and a filler metal that is fed
manually is usually used.
Gas Welding: In this method a focused high temperature flame generated by gas
combustion is used to melt the workpieces (and filler) together. The most common
type of gas welding is Oxy-fuel welding where acetylene is combusted in oxygen.
Resistance Welding: Resistance welding involves the generation of heat by passing
a high current (1000–100,000 A) through the resistance caused by the contact
between two or more metal surfaces where that causes pools of molten metal to
be formed at the weld area. The most common types of resistance welding are
Spot-welding (using pointed electrodes) and Seam-welding (using wheel-shaped
electrodes).
Energy Beam Welding: In this method a focused high-energy beam (Laser beam or
electron beam) is used to melt the workpieces and thus join them together.
Solid-State Welding: In contrast to other welding methods, solid-state welding
processes do not involve the melting of the materials being joined. Common types
of solid-state welding include; ultrasonic welding, explosion welding,
electromagnetic pulse welding, roll welding, friction welding (including friction-stir-
welding), etc.
Special technical language used in welding. The
basic terms of the welding language include:
1. Filler Material: When welding two pieces of metal together, we often have to leave
a space between the joint. The material that is added to fill this space during the
welding process is known as the filler material (or filler metal).
2. Welding Rod: The term welding rod refers to a form of filler metal that does not
conduct an electric current during the welding process. The only purpose of a welding rod is to supply filler metal to the joint. This type of filler metal is often used for gas welding.
3. Electrode: In electric-arc welding, the term electrode refers to the component that
conducts the current from the electrode holder to the metal being welded.
Electrodes are classified into two groups: consumable and non-consumable.
 Consumable electrodes not only provide a path for the current but they also
supply filler metal to the joint. An example is the electrode used in shielded
metal-arc welding.
 Non-consumable electrodes are only used as a conductor for the electrical
current, such as in gas tungsten arc welding. The filler metal for gas tungsten
arc welding is a hand fed consumable welding rod.
4. Flux: Before performing any welding process, the base metal must be cleaned form
impurities such as oxides (rust). Unless these oxides are removed by using a proper
flux, a faulty weld may result. The term flux refers to a material used to dissolve
oxides and release trapped gases and slag (impurities) from the base metal such
that the filler metal and the base metal can be fused together. Fluxes come in the
form of a paste, powder, or liquid.

THE IMPACT OF COVID-19 ON EDUCATION IN IMO STATE



ABSTRACT

This study examined the impact of covid-19 on education in Nigeria. This study was guided by the following objectives; to examine the impact of Covid-19 virus Nigerian Education system, to determine the relationship between COVID 19 virus pandemic and education in Nigeria, to evaluate the awareness of COVID-19 virus among students in Nigeria and to evaluate the after effect of Covid-19 pandemic on education system in Nigeria. The study employed the descriptive and explanatory design; questionnaires in addition to library research were applied in order to collect data. Primary and secondary data sources were used and data was analyzed using the chi square statistical tool at 5% level of significance which was presented in frequency tables and percentage. The respondents under the study were 100 residents of imo state, Nigeria. The study findings revealed that Covid-19 pandemic has significant impact on education in Nigeria; based on the findings from the study, schools need resources to rebuild the loss in learning during the pandemic.



CHAPTER ONE

INTRODUCTION

1.1 Background to the Study

Few months ago, the Director General of the World Health Organization (WHO) declared the outbreak of the coronavirus disease 2019 (COVID-19) on 30th January 2020 a Public Health Emergency of International Concern (PHEIC). In 2019, there was anxiety about the impact of a US-China trade war, the US presidential elections and Brexit on the World Economy. On account of these, the IMF had predicted moderated global growth of 3.4 percent. But COVID-19 – the disease caused by SARS-CoV-2, a novel strain of coronavirus from the SARS species – changed the outlook unexpectedly. Due to fear and uncertainty, and to rational assessment that firms’ profits are likely to be lower due to the impact of COVID-19, global stock markets erased about US$6 trillion in wealth in one week from 24th to 28th of February. The S&P 500 index lost over $5 trillion in value in the same week in the US while the S&P 500’s largest 10 companies experienced a combined loss of over $1.4 trillion (https://www.reuters.com), although some of these were recovered in the subsequent week. Some of the loss in value was due to rational assessment by investors that firms’ profits would decline due to the impact of the coronavirus.

Impact of covid 19 by Ibeku Valentine
The COVID-19 pandemic is first and foremost a health crisis. Many countries have (rightly) decided to close schools, colleges and universities. The crisis crystallises the dilemma policymakers are facing between closing schools (reducing contact and saving lives) and keeping them open (allowing workers to work and maintaining the economy). The severe short-term disruption is felt by many families around the world: home schooling is not only a massive shock to parents’ productivity, but also to children’s social life and learning. Teaching is moving online, on an untested and unprecedented scale. Student assessments are also moving online, with a lot of trial and error and uncertainty for everyone. Many assessments have simply been cancelled. Importantly, these interruptions will not just be a short-term issue, but can also have long-term consequences for the affected cohorts and are likely to increase inequality.

Impacts on education: Schools
Going to school is the best public policy tool available to raise skills. While school time can be fun and can raise social skills and social awareness, from an economic point of view the primary point of being in school is that it increases a child’s ability. Even a relatively short time in school does this; even a relatively short period of missed school will have consequences for skill growth. But can we estimate how much the COVID-19 interruption will affect learning? Not very precisely, as we are in a new world; but we can use other studies to get an order of magnitude.

Two pieces of evidence are useful. Carlsson et al. (2015) consider a situation in which young men in Sweden have differing number of days to prepare for important tests. These differences are conditionally random allowing the authors to estimate a causal effect of schooling on skills. The authors show that even just ten days of extra schooling significantly raises scores on tests of the use of knowledge (‘crystallized intelligence’) by 1% of a standard deviation. As an extremely rough measure of the impact of the current school closures, if we were to simply extrapolate those numbers, twelve weeks less schooling (i.e. 60 school days) implies a loss of 6% of a standard deviation, which is non-trivial. They do not find a significant impact on problem-solving skills (an example of ‘fluid intelligence’).

A different way into this question comes from Lavy (2015), who estimates the impact on learning of differences in instructional time across countries. Perhaps surprisingly, there are very substantial differences between countries in hours of teaching. For example, Lavy shows that total weekly hours of instruction in mathematics, language and science is 55% higher in Denmark than in Austria. These differences matter, causing significant differences in test score outcomes: one more hour per week over the school year in the main subjects increases test scores by around 6% of a standard deviation. In our case, the loss of perhaps 3-4 hours per week teaching in maths for 12 weeks may be similar in magnitude to the loss of an hour per week for 30 weeks. So, rather bizarrely and surely coincidentally, we end up with an estimated loss of around 6% of a standard deviation again. Leaving the close similarity aside, these studies possibly suggest a likely effect no greater than 10% of a standard deviation but definitely above zero.

Impacts on education: Families
Perhaps to the disappointment of some, children have not generally been sent home to play. The idea is that they continue their education at home, in the hope of not missing out too much.

Families are central to education and are widely agreed to provide major inputs into a child’s learning, as described by Bjorklund and Salvanes (2011). The current global-scale expansion in home schooling might at first thought be seen quite positively, as likely to be effective. But typically, this role is seen as a complement to the input from school. Parents supplement a child’s maths learning by practising counting or highlighting simple maths problems in everyday life; or they illuminate history lessons with trips to important monuments or museums. Being the prime driver of learning, even in conjunction with online materials, is a different question; and while many parents round the world do successfully school their children at home, this seems unlikely to generalise over the whole population.

So while global home schooling will surely produce some inspirational moments, some angry moments, some fun moments and some frustrated moments, it seems very unlikely that it will on average replace the learning lost from school. But the bigger point is this: there will likely be substantial disparities between families in the extent to which they can help their children learn. Key differences include (Oreopoulos et al. 2006) the amount of time available to devote to teaching, the non-cognitive skills of the parents, resources (for example, not everyone will have the kit to access the best online material), and also the amount of knowledge – it’s hard to help your child learn something that you may not understand yourself. Consequently, this episode will lead to an increase in the inequality of human capital growth for the affected cohorts.[color=#000099][/color]

The COVID-19 pandemic is first and foremost a health crisis. Many countries have (rightly) decided to close schools, colleges and universities. The crisis crystallises the dilemma policymakers are facing between closing schools (reducing contact and saving lives) and keeping them open (allowing workers to work and maintaining the economy). The severe short-term disruption is felt by many families around the world: home schooling is not only a massive shock to parents’ productivity, but also to children’s social life and learning. Teaching is moving online, on an untested and unprecedented scale. Student assessments are also moving online, with a lot of trial and error and uncertainty for everyone. Many assessments have simply been cancelled. Importantly, these interruptions will not just be a short-term issue, but can also have long-term consequences for the affected cohorts and are likely to increase inequality.

Impacts on education: Schools
Going to school is the best public policy tool available to raise skills. While school time can be fun and can raise social skills and social awareness, from an economic point of view the primary point of being in school is that it increases a child’s ability. Even a relatively short time in school does this; even a relatively short period of missed school will have consequences for skill growth. But can we estimate how much the COVID-19 interruption will affect learning? Not very precisely, as we are in a new world; but we can use other studies to get an order of magnitude.

Two pieces of evidence are useful. Carlsson et al. (2015) consider a situation in which young men in Sweden have differing number of days to prepare for important tests. These differences are conditionally random allowing the authors to estimate a causal effect of schooling on skills. The authors show that even just ten days of extra schooling significantly raises scores on tests of the use of knowledge (‘crystallized intelligence’) by 1% of a standard deviation. As an extremely rough measure of the impact of the current school closures, if we were to simply extrapolate those numbers, twelve weeks less schooling (i.e. 60 school days) implies a loss of 6% of a standard deviation, which is non-trivial. They do not find a significant impact on problem-solving skills (an example of ‘fluid intelligence’).

A different way into this question comes from Lavy (2015), who estimates the impact on learning of differences in instructional time across countries. Perhaps surprisingly, there are very substantial differences between countries in hours of teaching. For example, Lavy shows that total weekly hours of instruction in mathematics, language and science is 55% higher in Denmark than in Austria. These differences matter, causing significant differences in test score outcomes: one more hour per week over the school year in the main subjects increases test scores by around 6% of a standard deviation. In our case, the loss of perhaps 3-4 hours per week teaching in maths for 12 weeks may be similar in magnitude to the loss of an hour per week for 30 weeks. So, rather bizarrely and surely coincidentally, we end up with an estimated loss of around 6% of a standard deviation again. Leaving the close similarity aside, these studies possibly suggest a likely effect no greater than 10% of a standard deviation but definitely above zero.

Impacts on education: Families
Perhaps to the disappointment of some, children have not generally been sent home to play. The idea is that they continue their education at home, in the hope of not missing out too much.

Families are central to education and are widely agreed to provide major inputs into a child’s learning, as described by Bjorklund and Salvanes (2011). The current global-scale expansion in home schooling might at first thought be seen quite positively, as likely to be effective. But typically, this role is seen as a complement to the input from school. Parents supplement a child’s maths learning by practising counting or highlighting simple maths problems in everyday life; or they illuminate history lessons with trips to important monuments or museums. Being the prime driver of learning, even in conjunction with online materials, is a different question; and while many parents round the world do successfully school their children at home, this seems unlikely to generalise over the whole population.

So while global home schooling will surely produce some inspirational moments, some angry moments, some fun moments and some frustrated moments, it seems very unlikely that it will on average replace the learning lost from school. But the bigger point is this: there will likely be substantial disparities between families in the extent to which they can help their children learn. Key differences include (Oreopoulos et al. 2006) the amount of time available to devote to teaching, the non-cognitive skills of the parents, resources (for example, not everyone will have the kit to access the best online material), and also the amount of knowledge – it’s hard to help your child learn something that you may not understand yourself. Consequently, this episode will lead to an increase in the inequality of human capital growth for the affected cohorts.

The COVID-19 pandemic is first and foremost a health crisis. Many countries have (rightly) decided to close schools, colleges and universities. The crisis crystallises the dilemma policymakers are facing between closing schools (reducing contact and saving lives) and keeping them open (allowing workers to work and maintaining the economy). The severe short-term disruption is felt by many families around the world: home schooling is not only a massive shock to parents’ productivity, but also to children’s social life and learning. Teaching is moving online, on an untested and unprecedented scale. Student assessments are also moving online, with a lot of trial and error and uncertainty for everyone. Many assessments have simply been cancelled. Importantly, these interruptions will not just be a short-term issue, but can also have long-term consequences for the affected cohorts and are likely to increase inequality.

Impacts on education: Schools
Going to school is the best public policy tool available to raise skills. While school time can be fun and can raise social skills and social awareness, from an economic point of view the primary point of being in school is that it increases a child’s ability. Even a relatively short time in school does this; even a relatively short period of missed school will have consequences for skill growth. But can we estimate how much the COVID-19 interruption will affect learning? Not very precisely, as we are in a new world; but we can use other studies to get an order of magnitude.

Two pieces of evidence are useful. Carlsson et al. (2015) consider a situation in which young men in Sweden have differing number of days to prepare for important tests. These differences are conditionally random allowing the authors to estimate a causal effect of schooling on skills. The authors show that even just ten days of extra schooling significantly raises scores on tests of the use of knowledge (‘crystallized intelligence’) by 1% of a standard deviation. As an extremely rough measure of the impact of the current school closures, if we were to simply extrapolate those numbers, twelve weeks less schooling (i.e. 60 school days) implies a loss of 6% of a standard deviation, which is non-trivial. They do not find a significant impact on problem-solving skills (an example of ‘fluid intelligence’).

A different way into this question comes from Lavy (2015), who estimates the impact on learning of differences in instructional time across countries. Perhaps surprisingly, there are very substantial differences between countries in hours of teaching. For example, Lavy shows that total weekly hours of instruction in mathematics, language and science is 55% higher in Denmark than in Austria. These differences matter, causing significant differences in test score outcomes: one more hour per week over the school year in the main subjects increases test scores by around 6% of a standard deviation. In our case, the loss of perhaps 3-4 hours per week teaching in maths for 12 weeks may be similar in magnitude to the loss of an hour per week for 30 weeks. So, rather bizarrely and surely coincidentally, we end up with an estimated loss of around 6% of a standard deviation again. Leaving the close similarity aside, these studies possibly suggest a likely effect no greater than 10% of a standard deviation but definitely above zero.

Impacts on education: Families
Perhaps to the disappointment of some, children have not generally been sent home to play. The idea is that they continue their education at home, in the hope of not missing out too much.

Families are central to education and are widely agreed to provide major inputs into a child’s learning, as described by Bjorklund and Salvanes (2011). The current global-scale expansion in home schooling might at first thought be seen quite positively, as likely to be effective. But typically, this role is seen as a complement to the input from school. Parents supplement a child’s maths learning by practising counting or highlighting simple maths problems in everyday life; or they illuminate history lessons with trips to important monuments or museums. Being the prime driver of learning, even in conjunction with online materials, is a different question; and while many parents round the world do successfully school their children at home, this seems unlikely to generalise over the whole population.

So while global home schooling will surely produce some inspirational moments, some angry moments, some fun moments and some frustrated moments, it seems very unlikely that it will on average replace the learning lost from school. But the bigger point is this: there will likely be substantial disparities between families in the extent to which they can help their children learn. Key differences include (Oreopoulos et al. 2006) the amount of time available to devote to teaching, the non-cognitive skills of the parents, resources (for example, not everyone will have the kit to access the best online material), and also the amount of knowledge – it’s hard to help your child learn something that you may not understand yourself. Consequently, this episode will lead to an increase in the inequality of human capital growth for the affected cohorts.

RELIABILITY OF THE INSTRUMENTS
S/N Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12
1 1 1 1 1 1 1 1 1 1 0 1 1
2 1 0 1 1 1 1 1 1 1 1 0 0
3 1 1 1 1 1 1 1 1 1 1 1 1
4 1 1 1 0 1 1 0 0 1 1 0 1
5 1 0 1 1 1 1 1 1 1 1 1 1
6 1 1 1 1 1 1 1 1 1 1 1 1
7 0 1 0 1 1 1 0 1 1 1 1 0
8 1 1 1 1 0 1 1 1 1 1 1 1
9 1 0 1 0 1 1 1 1 1 1 1 1
10 0 1 1 1 1 0 1 1 0 1 1 1
11 1 1 1 1 1 1 1 1 1 1 1 0
12 1 1 1 1 1 1 1 0 1 1 1 1
13 1 1 1 1 1 1 0 1 0 1 0 1
14 0 0 0 0 0 1 1 1 1 1 1 1
15 1 1 1 1 1 1 1 1 1 1 1 1
16 0 1 1 1 1 1 0 1 1 1 1 0
17 1 0 1 1 1 1 1 1 1 1 0 1
18 1 1 1 1 1 1 1 0 1 1 1 1
19 1 0 3 1 1 1 1 1 1 0 1 1
20 0 1 1 1 0 1 1 1 0 1 1 0

Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 Q25
1 1 1 1 1 1 1 1 0 1 1 1 1
1 1 0 1 1 1 1 1 0 1 0 1 1
1 1 1 1 1 1 1 1 0 1 1 1 0
1 0 1 1 1 1 0 0 0 1 1 1 1
1 0 1 1 1 1 1 0 0 1 1 1 1
1 1 0 1 1 1 0 1 1 1 0 1 1
1 0 1 1 1 1 0 0 1 1 1 1 0
1 1 0 0 0 0 1 1 1 1 1 1 1
1 1 0 1 0 1 1 1 1 0 1 0 1
1 1 0 1 0 1 1 1 0 0 1 0 1
0 1 1 1 1 1 1 1 1 0 1 1 1
0 1 0 1 0 1 1 0 1 0 1 1 0
0 1 0 1 0 1 1 1 1 1 1 1 1
1 1 1 0 1 0 0 1 1 1 1 1 1
1 1 1 1 1 0 1 1 0 1 1 1 0
1 1 1 1 1 1 1 1 1 1 1 0 0
1 0 1 1 0 1 1 0 1 0 0 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1
1 1 1 0 1 0 1 1 1 1 1 0 1

Scale: KUDER-RICHARDSON 20

Reliability Statistics for MAT
Kuder-Richardson 20 N of Items
.714 25

The coefficient of 0.71 shows that the instrument is reliable.

S/N Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18
1 3 2 2 2 2 2 2 1 3 3 2 1 2 3 2 3 2 2
2 3 3 2 2 3 2 2 3 2 2 3 1 3 1 2 2 2 3
3 3 2 1 2 1 3 3 1 2 3 1 2 3 1 2 3 3 1
4 3 2 1 1 3 3 2 2 1 2 1 2 3 3 2 2 3 2
5 3 2 1 1 3 3 3 3 2 3 1 3 2 3 3 3 3 3
6 3 3 3 1 2 3 1 2 3 3 1 3 1 3 3 2 3 3
7 3 2 3 1 3 2 3 1 3 3 1 3 3 1 3 3 2 3
8 3 2 2 2 3 2 3 1 3 3 2 2 1 2 3 2 3 3
9 3 3 3 2 2 3 3 3 3 1 3 3 1 3 3 3 3 3
10 2 2 1 1 3 3 2 1 3 3 1 3 1 3 3 3 3 1
11 2 2 2 3 3 2 2 2 2 3 1 3 3 3 3 1 3 1
12 3 2 2 2 2 2 2 1 3 3 2 1 2 3 2 3 2 2
13 3 3 2 2 3 2 2 3 2 2 3 1 3 1 2 2 2 3
14 3 2 1 2 1 3 3 1 2 3 1 2 3 1 2 3 3 1
15 3 2 1 1 3 3 2 2 1 2 1 2 3 3 2 2 3 2
16 3 2 1 1 3 3 3 3 2 3 1 3 2 3 3 3 3 3
17 3 3 3 1 2 3 1 2 3 3 1 3 1 3 3 2 3 3
18 3 2 3 1 3 2 3 1 3 3 1 3 3 1 3 3 2 3
19 3 2 2 2 3 2 3 1 3 3 2 2 1 2 3 2 3 3
20 3 3 3 2 2 3 3 3 3 1 3 3 1 3 3 3 3 3


Reliability Statistics
Cronbach's Alpha N of Items
.789 18

The coefficient of 0.79 shows that the instrument is reliable.

Introduction
Physics in Nigeria are sometimes taught by a lecture approach without laboratory activities. This is described as a “Chalk and talk teaching approach, despite the fact that the West African Examination Council mandated that because of its very empirical nature, physics must be studied by aid of the laboratory classes, this was not being done. Also, the West African Council on science education noted in its 1969 annual report that physics was not being studied or taught with the aid of laboratory activities in Nigeria secondary schools. Students who are taught physics by the chalk and talk lecture approach have repeatedly demonstrated poor student motivation and achievement in and from their physics education programme. This is evidenced by the poor results in both the internal and external examination. The number and quality of passes in WACE physics examination from 1966 –up to date as externally unsatisfactory. The problem of poor achievement by Nigeria Secondary School physics students is wide spread and consistent. It is possible that these physics candidate did poorly in the council’s physics examination because they were taught this subject by lectures alone rather than subject without practical in the laboratory. Ali, (2014) noted that lectures alone do not provide the students the opportunity to comprehend, apply and analyze physics problems. Hence, they probably do poorly in theses higher cognitive hierarchies in their secondary school physics examination.
Physics as one of the branches of science is one of the science subjects in the secondary school curriculum. It performs some vital roles which help in the achievement of some national goals. In fact, physics is the basic sciences subject that deals with those fundamental questions on the structure of matter and interaction of elementary constituents of nature that are susceptible to experimental investigation and theoretically inquiry.
Physics as one of the science subjects has remained one of the most difficult subject in the school curriculum (NERD, 2014). A study by Owolabi, (2014) revealed that the performance of Nigeria students in ordinary level physics was generally poor, which he attributed to many factors including teaching strategy; it was considered an important factor. Jegede O. J., Okota O.E., and Eniayeju, P.A., (2010) reported factors responsible for students general poor performance in physics as; poor laboratory facilities, inability of physics teacher to put across ideas clearly to the students and inadequate number of learning facilities in school as against consistent increase in the number of students.
The mastery of physics concepts cannot be fully achieved without the use of the laboratory. The teaching of physics without learning materials (laboratory equipment), will certainly result to poor performance in the subject.
The laboratory consists of various tools and equipment used by scientist/science student’s either for the finding of new knowledge or to ascertain previous findings. Physics laboratory is a place where different types of experiment and researches concerning all the discipline of physics take place. Laboratory classes enhance a meaningful learning of science concept and theories (Seweje, 2010; Oluber and Unyimadu, 2011). Physics laboratory have been found to be a primary vehicle for promoting formal reasoning skill and students understanding, thereby enhancing desired learning outcome in students Ogunleye, (2012).
The laboratory classes help in increasing the achievement of students in learning and understanding the subject physics.
Finally, laboratory classes motivate students to learn physics thereby increases their academic performance.

Statement of the problem
Throughout the years, using laboratory for physics classes in Nigeria has not being encouraging hence thorough investigation into the factors that can enhance laboratory classes, motivate students and level of achievement in physics.
Purpose of the Study
The purpose of the research study is to identify the factors that motivate students and level of their achievement in laboratory classes.
1. To improve learning that stimulates positive impact towards the study of physics in the laboratory.
2. To inculcate scientific reasoning among physics students that helps to motivate and enhance great achievement.
3. To build the relationship between students and physics teachers during laboratory classes.
4. To enhance motivation and level of achievement in physics.
Research questions
1. Does a laboratory class help in teaching of physics?
2. Does laboratory classes motivate students thereby stimulates positive impact towards the study of physics?
3. Is there any significant relationship between students and teacher during laboratory classes?
4. Does a physics laboratory class helps to inculcate scientific reasoning among physics students?
5. Does a physics laboratory class enhance the student’s achievement in physics?


Scope of the Study
This research work is the laboratory classes, motivation and level of achievement in physics among five streams of SS1 students of Alvana model secondary school Owerri Imo state.
Methodology
The research design, population of the study, sample and sampling techniques, research instrument, validity of the instrument, method of data collection and method of data analysis will be discuss below.

Research design
The design of the study is descriptive survey, because it is only interested in describing and collecting data on facts about laboratory classes, motivation and level of achievement in physics.
Population of the Study
The population of the study consists of five streams of SS1 students of Alvana model secondary school Owerri, Imo State Wifu 2500, numbers of students.

Sample and Sampling Techniques
The sample was draw from five (5) streams of SS1 students of Alvana model secondary school owerri. A total of 250 students were randomly selected.
Research Instrument
The research instrument used for the study was structured students questionnaire (SSQ). The questionnaire consists of 18 items constructed a two points scare “Yes” or “No”. It was divided into A and B. Section A dealt with background information. The name class, Age, Sex while Section B solicited for the information on the impact of physics laboratory classes, motivation and level of achievement in physics. The questionnaire design with 18 items how laboratory classes can motivate and enhance student’s performance in physics.

Validity of the Instrument (SSQ)
The instrument was validated by expert in physics who ascertain whether the questions were relevant, clear and unambiguous.
Method of Data Collection
The questionnaire was distributed by the researcher to the students (respondents). The questionnaire was administered to them to tick their responses and they were also collected immediately to avoid alternation. Two hundred Fifty questionnaires were administrated and recovered.
Method of Data Analysis
The response to the items posted in the questionnaire were collected and tabulated with regards to the response from each class in order to answer each research question. In the analysis of the data collected simple percentage was used.


Result and Discussion
This section is concerned with the analysis of data collected from five streams of SS1 students; the summary table the results of the analysis, while all the calculation leading to the results are stated below.

Discussion of Findings
1. Does a laboratory class help in teaching of physics.
Table 1: Students responses.


Yes % No %
1 Stream 1 30 60 20 40
2 Stream 2 34 68 16 32
3 Stream 3 45 90 5 10
4 Stream 4 35 70 15 30
5 Stream 5 40 80 10 20
Total 184 73.6 66 26.4

The findings in the table above (table 1) revealed that physics laboratory classes helps in the teaching of physics students in Alvana Model Secondary School because 73.6% of the respondents agreed to the statement which is in consonance with Tatli, Z. H., (2010) whose finding that laboratory classes/ equipment reduces or eliminate individual difference in a way, because all equipment and methods used is doing experiment in laboratory studies are also element of individual training.
2. Does laboratory classes motivate students thereby stimulates positive impact toward the study of physics
Table 2: students responses

Yes % No %
1 Stream 1 37 74 13 26
2 Stream 2 44 88 6 12
3 Stream 3 49 98 1 2
4 Stream 4 30 60 20 40
5 Stream 5 40 80 10 20
Total 200 80.0 50 20.4

Table 2 revealed that physics laboratory classes improve learning that stimulate positive impact towards the study of physics among students in Alvana model secondary school, because 80.0% agreed with the statement while 20.4% disagreed with the statement. This can also be related with the work of Kallats, (2011) that seems practical work done in laboratory as a means to verify a science principle or theory already known to the students.
3. Is there any significant relationship between students and teacher during laboratory classes.

Table 3: students responses

Yes % No %
1 Stream 1 43 86 7 14
2 Stream 2 50 100 --- ---
3 Stream 3 50 100 ---- ----
4 Stream 4 50 100 ---- ----
5 Stream 5 30 60 20 40
Total 223 89.2 27 10.8

From the table 3, 89.2% agreed and 10.8% disagreed with the statement that there is a significant relationship between students and teacher during laboratory classes. The result reveals that there is significant relationship as compared with the work of Huan, A., Haur, S.C., and Biaowen, (2011) which stated that the laws of physics are found on experiment and that experiment done during laboratory classes are integral part of physics education and it takes a great deal of effort to pursue students to be more enthusiastic towards laboratory classes.








4. Does laboratory classes helps to inculcate scientific reasoning among physics students.
Table 4 students’ responses

Yes % No %
1 Stream 1 30 60 20 40
2 Stream 2 50 100
3 Stream 3 40 80 10 20
4 Stream 4 50 100
5 Stream 5 38 76 12 24
Total 208 83.2 42 16.8

Table 4 revealed that physics laboratory classes’ helps to inculcate scientific reasoning among physics students in Vilay, and Popu, (2018) stated also that practical activities enhance the understanding of physics theory and phenomena.
4. Does physics laboratory classes enhance the students performance in physics.





Table 5. Students responses.

Yes % No %
1 Stream 1 30 60 20 40
2 Stream 2 32 64 18 36
3 Stream 3 40 80 10 20
4 Stream 4 40 80 10 20
5 Stream 5 49 98 1 2
Total 191 76.4 59 23.6

The finding in table 5 reveals that physics laboratory classes enhances student’s performance in physics which leads to increase in level of achievement. The table discloses that 76.4% are in agreement. This also help to authenticate the works of Mustapha (2012) which states that laboratory classes provides learners with the opportunities to use scientific equipment to develop basic manipulative skills and practice investigative and develop problem solving attitudes needed for future work in science. The level of achievement is encouraging by these findings.
Summary and Conclusion
Based on the finding of the study
 The non-availability of laboratory equipment has great effect on the achievement level of students in physics.
 Student’s interests or motivation for the subject is affected by the numbers of practical classes they are exposed to per week in the laboratory.
 Student’s acquisition of skills is motivated by their participation in practical classes.
The widely uses of laboratory in science education are:
 To get students to comprehend abstract and complex scientific concepts by using concerts materials.
 To gain students problem solving analyzing skill by comprehend the nature of science.
 To develop practical experience and talents of students.

















Reference
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The great son of Umuahia Ibeku Valentine former Eze of Umuahia Students Association (USA) on Easter Monday join hearts in marriage with Lynda