An Ubiquitous Online System to Evaluate User Self-efficacy and Anxiety on Distance Learning
Chapter One
AIMS AND OBJECTIVES OF THE STUDY
The aims of this study include;
- Developing a self-efficacy evaluation facility.
- Helping with overcoming anxiety for distance learners.
The objectives of this study include:
- Examining related texts and research material in similar scope of study
- Examining the Software Life Cycle methodology that works best to implement the software.
- Finding out the best programming tools to best implement it.
CHAPTER TWO
REVIEW OF LITERATURE
This chapter examines in detail, the history and developments made in ICT social communication and distance learning, previous research work on this subject, the characteristics, models, architectures and limitations as pointed out by various scholars and researchers. This will provide the ground work for figuring out an efficient way to implement an active evaluation system.
OVERVIEW OF USER SELF EFFICACY
Use of technology sometimes has unpleasant side effects, which can include strong, negative emotional states that arise not only during interaction but even before, when the thought of getting to interact with the computer begins. Frustration, confusion, anger, anxiety, and similar emotional states can affect not only the interaction itself, but also productivity, learning, social relationships, and overall well-being. There are variety of related definitions explaining what anxiety is:
Leso and Peck (1992) define computer anxiety “as a sense of being fearful or apprehensive when using or considering the utilization of a computer.” Evidently, factors like the context in which an individual was first introduced to the computer (Brosnan, 1998a, 1998b; Rosen & Weil, 1995), past failure and successes with hardware or software, and the current tasks being attempted, including the use of a new computer applications (Saadé & Otrakji, 2007), are all determinants of the state and type of anxiety the individual is experiencing. These researchers have attempted to predict those that will experience computer anxiety by identifying factors that correlate with its occurrence. Frequently, such factors as selfefficacy and attitudes towards computer usage are posited as influencing the computer anxiety (Ayersman & Reed, 1995; Igbaria & Chakrabarti, 1990; Reed, Ayersman, & Liu, 1996). There are three sorts of anxieties: trait, state, and concept-specific.
Trait anxiety is defined as a general pervasive anxiety that is experienced by a person over the entire range of life experience. People who exhibit trait anxiety are chronically anxious and constantly under tension regardless of their situation. This anxiety is frequently used as a construct for personality, learning theory, and psychopathology. Trait anxiety defines a personality characteristic and may be inherited (Howard & Smith, 1986).
State anxiety is experienced as anxiety that fluctuates over time and arises to a responsive situation. State anxiety is related to a person’s learning background. A person may have experienced some anxiety in a situation and that anxiety is transferred to a similar situation.
Concept-specific anxiety is a transitory-neurotic sort of anxiety. Concept-specific anxiety is that the range between the trait and state anxieties. it’s an anxiety that’s related to a selected situation. Therefore, computer anxiety may be a concept-specific anxiety because it’s a sense that’s related to a person’s interaction with computers (Oetting, 1983). Howard and Smith (1986) further define computer anxiety “as the tendency of an individual to experience A level of uneasiness over his or her impending use of a computer.”
In information systems study, anxiety has been viewed as a personality variable that influences system use (Agarwal & Karahanna, 2000). variety of IS studies are according to the view that the connection between anxiety and behavior is mediated by the private beliefs (Schlenker & Leary, 1982) and anxiety is incorporated as an antecedent to the beliefs of usefulness and simple use (e.g., Igbaria, 1993; Venkatesh & Davis, 2000). it’s interesting to notice that classical view of hysteria is that it mediates the connection between beliefs and behavior (Spielberger, 1972). Thus, anxiety are often viewed as a results of the beliefs a private has, instead of as an antecedent to them. for instance , a private who features a belief that s/he are going to be embarrassed by delivering a speech has speech anxiety (commonly called stage fright); as a results of the anxiety, s/he refuses to offer speeches. the assumption results in the fear (i.e., anxiety), which results in the behavior (i.e., avoidance). Following an equivalent line of reasoning, one could presume that a student (in some cases) who features a belief that s/he will experience technological problems while doing a web test has computer anxiety; as a results of the anxiety, s/he are going to be paranoid about computer problems while doing the web test. the assumption results in fear, which results in the behavior of paranoia, thereby causing the scholar to be less focused on doing the test (leading to reduced performance).
Igbaria and Parasuraman (1989) apply these theories and define computer anxiety “as the tendency of people to be uneasy, apprehensive, or fearful about current or future use of computers”. variety of studies have provided evidence supporting an immediate relationship between computer anxiety and computer use (Brosnan, 1999; S. L. Chau, Chen, & Wong, 1999; Howard & Mendelow, 1991; Igbaria, Parasuraman, & Baroudi, 1996). the pc anxiety research clearly shows that a highly computer anxious individual are going to be at a big disadvantage compared to his/her peers. One example of such an environment is an e-learning offered by many higher learning institutions.
Anxiety & Perceived Ease of Use
Prior research has shown that past experience is a determinant of behavior (Ajzen & Fishbein, 1980). In general, TAM identifies the relationships between PEU, PU, attitude (ATT), and behavioral intentions (BI) towards a target system (Davis et al., 1989). In the context of the present elearning study, perceived ease of use (PEU) refers to the degree to which the student expects the LMS to be free from cognitive effort (Davis et al., 1989). Enhanced course performance implies that the student can obtain a better grade by using the LMS without any usage difficulties (Igbara & Tan, 1997, Saadé & Bahli, 2005). Students’ perception of enhanced performance affects attitudes. In other words, students that perceive the system to be easy to use, develop better attitudes towards the LMS as reported by previous studies (Adams, Nelson, & Todd, 1992; Pedersen & Nysveen, 2003; Saadé & Kira, 2007). Specifically we make the following hypothesis (H1) related to ANX and PEU, shown in Figure 1.
REFERENCES
- Adams, D. A., Nelson, R. R., & Todd, A. P. (1992). Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Quarterly 16(2), 227-247.
- Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior.Englewood Cliffs, NJ: Prentice-Hall.
- Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly 24(4), 665-694.
- Ayersman, D. J., & Reed, W. M. (1995). Effects of learning styles, programming, and gender on computer anxiety. Journal of Research on Computing in Education,28(2), 148-161.
- Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change.Psychological Review, 84(2), 191-215.
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- Bandura A. (1982) Self-efficacymechanism in human agency. Journal of American Psychology, 37, 122-
