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Journal articles on the topic 'Computer instruction'

Author: Grafiati

Published: 4 June 2021

Last updated: 31 January 2023

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1

Omoniyi, Tayo, and Gisanrin Gbenga. "The Effect of Three Instructional Elements on Achievement in Computer-Based Mathematics Instruction of Senior Secondary School Students in Nigeria." Journal of Education in Black Sea Region 4, no. 1 (December 9, 2018): 164–72. http://dx.doi.org/10.31578/jebs.v4i1.163.

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This study investigated the effect of three instructional elements on achievement in computer-based mathematics instruction. The subjects were senior secondary school students who used four versions of computer-based instruction developed on compact disc to learn about the volume of solid shapes. The four versions of the programme were (1) a full version that had the three instructional elements (2) a version without objectives (3) a version without practice (4) a version without examples. The results indicated that the full package, which included objectives, practice and examples, had a significant effect on students’ achievement in the computer-based mathematics instruction. Furthermore, of the three elements, practice, had the most effect on the learners’ achievement. Implications of the findings on development of computer-based instructions are also discussed.

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Keengwe, Jared, and Farhan Hussein. "Computer-Assisted Instruction." International Journal of Information and Communication Technology Education 9, no. 1 (January 2013): 70–79. http://dx.doi.org/10.4018/jicte.2013010107.

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The purpose of this study was to examine the relationship in achievement gap between English language learners (ELLs) utilizing computer-assisted instruction (CAI) in the classroom, and ELLs relying solely on traditional classroom instruction. The study findings showed that students using CAI to supplement traditional lectures performed better than the students relying solely on traditional classroom instruction. In addition, using CAI to supplement traditional lectures helped the charter schools to close the educational achievement gap of their students. Based on the findings, there is need for teachers to move past traditional learning, and learn new technology skills in order to incorporate sound technology-enhanced instructional strategies to support student learning.

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Barrow, Lisa, Lisa Markman, and Cecilia Elena Rouse. "Technology's Edge: The Educational Benefits of Computer-Aided Instruction." American Economic Journal: Economic Policy 1, no. 1 (January 1, 2009): 52–74. http://dx.doi.org/10.1257/pol.1.1.52.

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We present results from a randomized study of a well-defined use of computers in schools, a popular instructional computer program for pre-algebra and algebra. We primarily assess the program using a test designed to target pre-algebra and algebra skills. Students randomly assigned to computer-aided instruction score significantly higher on a pre-algebra and algebra test than students randomly assigned to traditional instruction. We hypothesize that this effectiveness arises from increased individualized instruction as the effects appear larger for students in larger classes and in classes with high student absentee rates. (JEL H75, I21)

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Merrill, James D. "Computer Instruction." Music Educators Journal 87, no. 4 (January 2001): 8. http://dx.doi.org/10.2307/3399715.

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Milheim, William D. "Interactivity and Computer-Based Instruction." Journal of Educational Technology Systems 24, no. 3 (March 1996): 225–33. http://dx.doi.org/10.2190/9v8j-48tx-461c-dxvg.

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Interactivity is one of the most important factors in the design and development of effective computer-based instructional materials. The following article describes this instructional component, its overall purpose in various learning environments, benefits that can be gained from its utilization, and its specific use within computer-based instruction. A number of strategies are also provided to assist instructional designers in their utilization of this significant program element.

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Strot, Melody. "Individualizing Instruction with Computer Applications." Gifted Child Today 21, no. 2 (March 1998): 40–42. http://dx.doi.org/10.1177/107621759802100212.

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Although computers can be a terrific resource for all children, gifted children particularly benefit from the individualization provided by-different computer applications. For the gifted child who finishes written class exercises quickly, computer programs may extend subject matter. From my observations, however, teachers use computers primarily for drill and practice exercises and word processing.

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Rouse, Deborah P. "Computer-assisted instruction: An effective instructional method." Teaching and Learning in Nursing 2, no. 4 (October 2007): 138–43. http://dx.doi.org/10.1016/j.teln.2007.07.007.

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Guha, Smita. "Integrating Computers in Elementary Grade Classroom Instruction—Analyses of Teachers' Perceptions in Present and Preferred Situations." Journal of Educational Computing Research 24, no. 3 (April 2001): 275–303. http://dx.doi.org/10.2190/69w7-hptu-wmqv-m8p3.

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This study explored elementary grade teachers' personal experience with instructional computing and the role of computers they would like to see in classroom instruction. One hundred forty-nine teachers from 15 elementary schools randomly chosen from two counties in western New York participated in the study. Teachers answered a survey questionnaire on their training and knowledge in computers, their comfort level in using computers for teaching, and computer usage in classroom instruction. The teachers also answered to what extent do they prefer to receive more training, be more comfortable using computers, and integrate computers more in their teaching. Based on teachers' responses, significant differences and positive correlation were found between teachers' present computer training, level of comfort, and computer usage in the classrooms as compared to their preferred training, comfort, and usage.

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Skudrna, Vincent J. "Role of Computer Assisted Instruction (CAI) in an Introductory Computer Concepts Course." Journal of Educational Technology Systems 25, no. 4 (June 1997): 327–45. http://dx.doi.org/10.2190/8362-cgbb-3d5r-j0uc.

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The primary objective of this article is to discuss the role of Computer Assisted Instruction (CAI) at the undergraduate level via a survey of related literature and specific applications. CAI shares many features with other instructional modes, such as traditional classrooms and programmed instruction (PI). Many characteristics of learners affect their ability to learn and acquire new knowledge. An individual's subject-specific knowledge and general knowledge both affect comprehension. With regard to instructional design, system approaches are sometimes referred to as instructional development systems (IDS). An IDS embraces several major categories. These include a statement of goals, analysis, development of instruction, and evaluation and revision. General statements on CAI can be divided into the following areas: requirements, potential benefits, state of the art, problems, CAI as a factor in society, the roles of industry, education, and government, including the role of teacher. At least two educational requirements make CAI inevitable, i.e., the trend to individualized instruction and the growth in information to be acquired. Data processing and computer science involve the teaching of computer skills in relative isolation from other disciplines. Hence, the computer is the principal subject. Student problem solving and research is where the computer is used as a tool in some field outside computer science. A specific sphere of application is the subject. This article will relate these categories as they apply to an introductory computer concepts course taught at the undergraduate level. Another phase of this course is that it is accounting-oriented.

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Bottge, Brian A., Enrique Rueda, Timothy S. Grant, Ana C. Stephens, and Perry T. Laroque. "Anchoring Problem-Solving and Computation Instruction in Context-Rich Learning Environments." Exceptional Children 76, no. 4 (July 2010): 417–37. http://dx.doi.org/10.1177/001440291007600403.

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Middle school students with learning disabilities in math (MLD) used two versions of Enhanced Anchored Instruction (EAI). In one condition, students learned how to compute with fractions on an as-needed basis while they worked to solve the EAI problems. In the other condition, teachers used a computer-based instructional module in place of one of the EAI problems to deliver formal fraction instruction. The results indicated that students in both instructional formats improved their fraction computational skills and that formal instruction provided an added benefit. Both instructional conditions improved students' problem-solving skills by about the same amount. The findings suggest that combining formal fraction instruction with EAI is a viable way to improve the problem-solving and computational skills of students with MLD.

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Munyakazi, Jean Paul, Josiane Mukagihana, Theophile Nsengimana, Concilie Mukamwambali, and Olivier Habimana. "Impacts of Computer-Assisted Instructions on Students' Academic Performance of Biology within Secondary Schools." International Journal of Learning and Development 12, no. 2 (June 24, 2022): 81. http://dx.doi.org/10.5296/ijld.v12i2.19766.

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Computer-assisted instructions (CAI) not only motivate students to learn but also enable learners to learn by interacting with instructional tools that allow learners to react the way they would react in real situations. This study sought to investigate the impact of computer-assisted instruction on learners' achievement of biology with a focus on cell division topics. The study adopted a quasi-experimental design. The population of this study was all upper secondary students that have Biology in their learning subjects within the Nyagatare district. To get a sample, researchers purposively selected three schools on the condition that they are equipped with smart classrooms having connected computers. The researchers took one class at each school. Thus, we got a total of ninety (90) senior five learners. The researchers split these learners into two groups composed of 45 learners in the experimental group, and 45 students in the control group. Learners in the experimental group were subjected to computer-assisted instructions while learners in the control group went through the traditional lecturing instructions. To collect data, a biology performance test (BPT) was used. The reliability coefficient (Cronbach’s coefficient Alpha) calculated for the instrument was 0.704. Pre and post-tests were given to all students in both groups. We used the inferential statistics t-test to analyze the data. The results showed [t (88) = -6.640, p = .000; p<.05] indicating that there is a statistically significant difference in mean scores between groups. The findings from the study allowed us to conclude that computer-assisted instruction enhances students' performance in biology, especially in cell division. Therefore, we recommend the integration of computer-assisted instructions into teaching and learning to enhance learners’ performance in biology.

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12

Clark, Richard E. "Confounding in Educational Computing Research." Journal of Educational Computing Research 1, no. 2 (May 1985): 137–48. http://dx.doi.org/10.2190/hc3l-g6yd-bak9-eqb5.

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Despite considerable evidence in research that computer-based instruction enhances student learning, an argument is presented that most of this research is confounded. Wherever computers are used to deliver instruction (including the teaching of programming languages), any resulting change in student learning or performance may be attributed to the uncontrolled effects of different instructional methods, content and/or novelty. The evidence for this confounding places the independent variables in most of these studies in doubt and diminishes the role of educational computing research in the development of instructional theory but not in instructional development or delivery.

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Zendler, Andreas, and Manuel Gohl. "Direct Instruction vs. Computer Simulation and their Learning Outcome in Engineering Education." International Journal of Engineering Education 1, no. 2 (December 15, 2019): 91–98. http://dx.doi.org/10.14710/ijee.1.2.91-98.

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Answers to the questions of which instructional methods are suitable for school, what instructional methods should be applied in teaching individual subjects and how instructional methods support the act of learning represent challenges to general education and education in individual subjects. This study focuses on the empirical examination of learning outcome in engineering educationwith respect to two instructional methods: direct instruction and computer simulation. A CRF 2x2 design is used to control instructional method and class context. Learning outcome on bridge construction is assessed with reference to the optics of bridge and the material usage for the bridge. The empirical findings show that learning with direct instruction was superior to computer simulation.

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14

Stewart, William J. "Optimizing Computer-Integrated Instruction." Journal of Educational Technology Systems 18, no. 2 (December 1989): 103–7. http://dx.doi.org/10.2190/end4-4y3x-vxd6-xht2.

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Computer use has typically been relatively limited in elementary and secondary school classrooms. Nevertheless, the computer can and should be fully infused into the total instructional process. In line with this, the computer, through being programmed to generate, relative to the separate subject, broad fields and personal-social essentials curricular approaches, suggestions of objectives, content items, activities, materials, and evaluation devices, for better relating instruction within separate subjects and/or across subject lines to student differences, can become an integral part of the overall teaching-learning enterprise.

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15

Martin, DS. "Computer-assisted instruction." American Journal of Roentgenology 144, no. 1 (January 1985): 217. http://dx.doi.org/10.2214/ajr.144.1.217.

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Adler, Mark, Kevin M. Baumlin, and Lynne D. Richardson. "Computer-assisted Instruction." Academic Emergency Medicine 7, no. 12 (December 2000): 1440. http://dx.doi.org/10.1111/j.1553-2712.2000.tb00506.x.

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MacGregor, S. Kim. "Computer Programming Instruction." Journal of Research on Computing in Education 21, no. 2 (December 1988): 155–64. http://dx.doi.org/10.1080/08886504.1988.10781868.

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18

Beichner, Robert J. "Computer-Assisted Instruction." Journal of Research on Computing in Education 24, no. 4 (June 1992): 571–72. http://dx.doi.org/10.1080/08886504.1992.10782028.

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Beichner, Robert J. "Computer-Assisted Instruction." Journal of Research on Computing in Education 24, no. 3 (March 1992): 571–72. http://dx.doi.org/10.1080/08886504.1992.10782632.

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20

&NA;, &NA;. "COMPUTER-ASSISTED INSTRUCTION." AJN, American Journal of Nursing 92, no. 6 (June 1992): 76–77. http://dx.doi.org/10.1097/00000446-199206000-00039.

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21

Hudson, Walter W. "Computer Managed Instruction." Computers in Human Services 1, no. 1 (January 18, 1985): 117–23. http://dx.doi.org/10.1300/j407v01n01_07.

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22

Jirka, Charles C., and Sharon E. Smaldino. "Computer Assisted Instruction." Middle School Journal 20, no. 4 (March 1989): 26–28. http://dx.doi.org/10.1080/00940771.1989.11495026.

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23

Anderson, Kathy. "Computer-assisted instruction." Journal of Medical Systems 10, no. 2 (April 1986): 163–71. http://dx.doi.org/10.1007/bf00993122.

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24

Opitz, Margaret. "Computer-Based Instruction." Clearing House: A Journal of Educational Strategies, Issues and Ideas 72, no. 1 (September 1998): 4–5. http://dx.doi.org/10.1080/00098659809599374.

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25

Kelly, Luke. "Computer Assisted Instruction." Journal of Physical Education, Recreation & Dance 58, no. 4 (April 1987): 74–79. http://dx.doi.org/10.1080/07303084.1987.10603873.

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26

Thach, Kim J., and Kimberly A. Norman. "Technology-Rich Mathematics Instruction." Teaching Children Mathematics 15, no. 3 (October 2008): 152–58. http://dx.doi.org/10.5951/tcm.15.3.0152.

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Over the past decade, technology—particularly computer technology—has become more accessible to students in public school settings. From 2000 to 2005, the ratio of students to computers with Internet access improved from approximately seven students per computer to four students per computer (Wells and Lewis 2006). Although access continues to increase, one of the remaining challenges is the successful integration of technology as a tool for facilitating learning across the curriculum.

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Harvey, T. Edward. "Computer-Assisted Spanish-Composition Instruction Survey—1986." CALICO Journal 4, no. 2 (January 14, 2013): 55–67. http://dx.doi.org/10.1558/cj.v4i2.55-67.

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This study reports on a survey of Spanish instructors' views on the use of computers in Spanish composition instruction. Data are reported for 208 (from a total of 1,678) full-time instructional faculty at universities, two-year colleges, and high schools across the nation. Most respondents taught one-semester courses whose enrollment sizes were increasing. Text use for the majority of programs is three years or less. This corresponds to the advent of process-model texts. Apples and IBM-PCs predominate among the hardware available. The lack of foreign-character support remains the major frustration reported. Essay analyzers are new to nearly everyone. There is mixed opinion about the real versus the expected benefits of using word processors as part of composition instruction. However, the time appears right for a paradigm shift and curriculum definition to include computer-assisted composition instruction.

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Brown, Ted, Brett Williams, Shapour Jaberzadeh, Louis Roller, Claire Palermo, Lisa McKenna, Caroline Wright, et al. "Predictors of attitudes to e‐learning of Australian health care students." Journal of Applied Research in Higher Education 2, no. 1 (January 1, 2010): 60–76. http://dx.doi.org/10.1108/17581184201000006.

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Computers and computer‐assisted instruction are being used with increasing frequency in the area of health science student education, yet students’ attitudes towards the use of e‐learning technology and computer‐assisted instruction have received limited attention to date. The purpose of this study was to investigate the significant predictors of health science students’ attitudes towards e‐learning and computer‐assisted instruction. All students enrolled in health science programmes (n=2885) at a large multi‐campus Australian university in 2006‐2007, were asked to complete a questionnaire. This included the Online Learning Environment Survey (OLES), the Computer Attitude Survey (CAS), and the Attitude Toward Computer‐Assisted Instruction Semantic Differential Scale (ATCAISDS). A multiple linear regression analysis was used to determine the significant predictors of health science students’ attitudes to e‐learning. The Attitude Toward Computers in General (CASg) and the Attitude Toward Computers in Education (CASe) subscales from the CAS were the dependent (criterion) variables for the regression analysis. A total of 822 usable questionnaires were returned, accounting for a 29.5 per cent response rate. Three significant predictors of CASg and five significant predictors of CASe were found. Respondents’ age and OLES Equity were found to be predictors on both CAS scales. Health science educators need to take the age of students and the extent to which students perceive that they are treated equally by a teacher/tutor/instructor (equity) into consideration when looking at determinants of students’ attitudes towards e‐learning and technology.

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Longmuir, Kenneth J. "Interactive computer-assisted instruction in acid-base physiology for mobile computer platforms." Advances in Physiology Education 38, no. 1 (March 2014): 34–41. http://dx.doi.org/10.1152/advan.00083.2013.

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In this project, the traditional lecture hall presentation of acid-base physiology in the first-year medical school curriculum was replaced by interactive, computer-assisted instruction designed primarily for the iPad and other mobile computer platforms. Three learning modules were developed, each with ∼20 screens of information, on the subjects of the CO2-bicarbonate buffer system, other body buffer systems, and acid-base disorders. Five clinical case modules were also developed. For the learning modules, the interactive, active learning activities were primarily step-by-step learner control of explanations of complex physiological concepts, usually presented graphically. For the clinical cases, the active learning activities were primarily question-and-answer exercises that related clinical findings to the relevant basic science concepts. The student response was remarkably positive, with the interactive, active learning aspect of the instruction cited as the most important feature. Also, students cited the self-paced instruction, extensive use of interactive graphics, and side-by-side presentation of text and graphics as positive features. Most students reported that it took less time to study the subject matter with this online instruction compared with subject matter presented in the lecture hall. However, the approach to learning was highly examination driven, with most students delaying the study of the subject matter until a few days before the scheduled examination. Wider implementation of active learning computer-assisted instruction will require that instructors present subject matter interactively, that students fully embrace the responsibilities of independent learning, and that institutional administrations measure instructional effort by criteria other than scheduled hours of instruction.

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Craig, John S. "A Systematic Approach to Improving In-House Computer Literacy." Journal of Educational Technology Systems 21, no. 1 (September 1992): 51–70. http://dx.doi.org/10.2190/9n9k-4tw8-9tu9-70tc.

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Computer trainers and technical writers responsible for instructing end users on the proper use of in-house computer systems are challenged with a task that is becoming increasingly complex and vital to an organization's efficiency. Since in-house computer systems are custom-designed for use within organizations, classroom trainers, writers, and other technical communicators must provide comprehensive classroom instruction and documentation for users. This article cites recent research on computer training and writing strategies in the technical communication and instructional technology fields, and how these strategies can be used by technical communicators to instruct users of in-house computer systems. An in-house computer training model is presented to help technical communicators design in-house computer training sessions, improve existing sessions, and create and revise in-house, instructional computer user documentation.

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Corbett, Mona R., Christine D. Townsend, and Jayne M. Zajicek. "THE EFFECTIVENESS OF COMPUTER - ASSISTED INSTRUCTION IN A HORTICULTURE PLANT IDENTIFICATION CLASS." HortScience 27, no. 6 (June 1992): 673b—673. http://dx.doi.org/10.21273/hortsci.27.6.673b.

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Plant identification is a prerequisite to many, if not all, horticulturally related classes. It typically has been taught through the use of live specimens, slides, and text books. Recently, computers have entered the picture as a possible tool to teach plant identification. Increased availability and sophistication of computer systems in the college setting have led to the increased use of computers in instruction. The objective of this study was to determine if there was a relationship between a student's learning style and academic achievement following computer assisted instruction. Undergraduate students enrolled in a plant identification class were involved in the study. Students learned plant identification either by: 1) viewing live specimens, 2) utilizing a computer instruction database system, or 3) combining live specimens with computer instruction. The students' cognitive knowledge was evaluated with pre and post tests. Learning style and attitude toward computer assisted instruction were also obtained.

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Peled, Zimra, Elad Peled, and Gad Alexander. "A Taxonomy for Computer Software Adoption Policy." Journal of Educational Computing Research 8, no. 1 (February 1992): 81–100. http://dx.doi.org/10.2190/6kh9-deb1-kfn0-qyr6.

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This article proposes a taxonomy to aid decision makers in selecting computer software that is consistent with the their values and preferences for instruction. It builds on two interrelated arguments: 1) the nature of instruction and the use of information technology derive from a conceptual framework that is embedded in an explicit or implicit belief about the nature of human development and learning, and 2) due to the value nature of instruction, the instructional beliefs embedded in software should be congruent with the decision maker's beliefs underlying instruction. The taxonomy consists of three components: characteristics of patterns of instruction, properties of software, and the congruence between them. These components are interrelated in a mapping sentence [1] that maps characteristics of instruction onto properties of software. The taxonomy refers to two types of educational decision makers. Believers, whose decisions are predetermined by a belief commitment and orchestrators, whose decisions are heuristically taken. Decisions for believers are straight forward; decisions for orchestrators are more complicated and depend on contextual factors represented in the mapping sentence. Links between research findings and the taxonomy are presented and illustrate the taxonomy's use and its utility in predicting real world decisions.

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Olejnik, Stephen, and Linda Wang. "An Innovative Application of the Macintosh Classic II Computer for Distance Education." Journal of Educational Technology Systems 21, no. 2 (December 1992): 87–101. http://dx.doi.org/10.2190/afdf-fcm0-u1ww-a1y8.

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The present article describes an innovative application of microcomputers to provide instruction simultaneously to graduate students on campus and to a group of doctoral students located 100 miles from campus. Using Macintosh Classic II computers and supporting equipment, both groups were taught a two-course sequence on statistical methods over two ten-week quarters. Evaluative data indicated similar academic achievement in both groups and comparable performance to previous sections of the course. Student attitudes were mixed, with students on-campus being more critical of the approach than students off-campus. The instructional approach appears to provide a viable alternative solution to a difficult problem for distance education. The use of Macintosh Classic II computers to facilitate instruction over long distance provides an acceptable compromise between extensive travel by either students or an instructor.

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Torgesen, Joseph K., and Theodore A. Barker. "Computers as Aids in the Prevention and Remediation of Reading Disabilities." Learning Disability Quarterly 18, no. 2 (May 1995): 76–87. http://dx.doi.org/10.2307/1511196.

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This article provides examples of ways that computer-assisted instruction can help children with learning disabilities (LD) learn to read more effectively. Computer-assisted instruction and practice in reading is fit within an instructional model for LD children that recognizes their special needs for assistance in acquiring accurate and fluent word identification skills. The theory that reading disabilities are phonologically based is discussed as a context for focusing instruction on alphabetic reading skills. Computer programs that provide training in phonological awareness, specific context-free word identification skills, and reading of connected text are described, and preliminary evidence about their instructional effectiveness is presented.

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Larsen, Mark D. "PERSISTENT PROBLEMS OF COMPUTER-ASSISTED INSTRUCTION." CALICO Journal 1, no. 5 (January 14, 2013): 31–34. http://dx.doi.org/10.1558/cj.v1i5.31-34.

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The advent of computers divided the humanists into camps for and against the new technology. This article summarizes the arguments of both camps then suggests that recent technological advances have helped to overcome some of the arguments against the use of computers and have even added new visual and audio dimensions to its potential. The computer age has arrived, and education must meet the challenge or the students will be the losers.

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Rieth, Herbert, Christine Bahr, Cynthia Okolo, Lewis Polsgrove, and Robert Eckert. "An Analysis of the Impact of Microcomputers on the Secondary Special Education Classroom Ecology." Journal of Educational Computing Research 4, no. 4 (November 1988): 425–41. http://dx.doi.org/10.2190/c1rd-kybj-59rt-n68n.

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The purpose of this research was to examine the effects of microcomputers on the ecology of secondary special education classrooms. Observational data were collected in twenty-six secondary school special education classes located in an urban midwestern school system. The data indicated that despite the ready availability of computers, only approximately 60 percent of the teachers chose to use them for instruction and they were in use only 25.3 percent of the time. The infrequent use was attributed to the lack of appropriate software, logistical problems in scheduling the microcomputer, and lack of training and support for teachers. The use of microcomputers was found to be related to increased student active engagement and decreased off-task behaviors. Unfortunately, teachers who used computers spent less time engaged in direct instructional activities and did not integrate the computer-based instruction with the teacher-based instruction.

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Cates, Ward Mitchell. "The Importance of Subject Matter Instructional Expertise in Research on the Effectiveness of Instructional Computer Programs." Journal of Educational Technology Systems 21, no. 4 (June 1993): 363–67. http://dx.doi.org/10.2190/lgwl-5g88-p57m-6flc.

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This article examines the importance of subject matter instructional expertise in the design of research studies on computer-based instruction. It considers the implications of shifts in instructional focus from associationism toward cognitivism and points out how difficult it is for most researchers to be experts in both computer-based instructional design and subject matter content instruction. The article suggests that researchers need to work closely with subject matter instructional experts and need to document in their presentations and research articles that they recognized and addressed the importance of subject matter instructional expertise.

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Koroghlanian, Carol M., and Howard J. Sullivan. "Audio and Text Density in Computer-Based Instruction." Journal of Educational Computing Research 22, no. 2 (March 2000): 217–30. http://dx.doi.org/10.2190/5qvq-3xxq-x1jc-t2f2.

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This study investigated the effects of audio and text density on the achievement, time-in-program, and attitudes of 134 university undergraduate students. Data concerning the participants' pre-existing computer skills and experience, as well as demographic information, were also collected. The instruction in visual design principles was delivered by a CBI program and included numerous illustrations. Participants were randomly assigned to one of three presentation versions of the instruction: Text Only, Full Text-Full Audio, or Lean Text-Full Audio. No significant difference in achievement was found between the three treatment groups, however there was a significant difference in learning efficiency, with the Text Only group requiring significantly less instructional time and achieving as well on the posttest as each of the other two groups. Significant differences in achievement were obtained for overall computer experience (participants with more computer experience performed better than those with less) and gender (females performed better than males). Overall, attitudes toward the instruction were favorable with participants in the Full Text-Full Audio treatment responding less favorably than their counterparts in the other two treatments. The findings have implications for the use of audio, text and graphics in the instructional design of computer-based instruction.

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Martin, Florence, James D. Klein, and Howard Sullivan. "The impact of instructional elements in computer-based instruction." British Journal of Educational Technology 38, no. 4 (July 2007): 623–36. http://dx.doi.org/10.1111/j.1467-8535.2006.00670.x.

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Ugwuanyi, Christian Sunday, and Chinedu I. O. Okeke. "Enhancing University Students’ Achievement in Physics using Computer-Assisted Instruction." International Journal of Higher Education 9, no. 5 (July 17, 2020): 115. http://dx.doi.org/10.5430/ijhe.v9n5p115.

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Twenty-first century classrooms have come with a lot of changes in instructional delivery at various levels of education. However, most lecturers in Nigerian universities still adopt the traditional method of instruction not minding the demands of the twenty-first century classrooms. As a result of this, there is a dearth of empirical evidence on the impact of computer-assisted instruction on the students’ achievement in physics. This study, therefore, sought the efficacy of computer-assisted instruction (CAI) on students’ achievement in physics. A randomized controlled trial experimental design was adopted for the study using a sample of 120 participants. Physics Achievement Test (PAT) was used to collect data for the study. Analysis of covariance was used to analyze the data. It was found that Computer-Assisted Instruction (CAI) had a significant effect on students’ achievement in physics at posttest and follow-up assessments. Thus, Physics education lecturers should be trained on how to design and use CAI package for effective twenty-first century classroom instructional delivery in Nigerian university.

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41

Colorado, Rafael J. "Computer-Assisted Instruction Research." Journal of Research on Computing in Education 20, no. 3 (March 1988): 226–33. http://dx.doi.org/10.1080/08886504.1988.10781837.

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42

Linden, Jan, and Egbert M. H. Assink. "Designing Computer-Aided Instruction." Performance Improvement Quarterly 3, no. 2 (October 22, 2008): 65–76. http://dx.doi.org/10.1111/j.1937-8327.1990.tb00458.x.

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Klein, P. J. "CARDIOPULMONARY COMPUTER-ASSISTED INSTRUCTION." Cardiopulmonary Physical Therapy Journal 6, no. 4 (1995): 5. http://dx.doi.org/10.1097/01823246-199506040-00005.

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44

Smith, T. Michael, and Kenneth Andrews. "Computer-Assisted Video Instruction:." Computers in the Schools 2, no. 1 (April 26, 1985): 65–74. http://dx.doi.org/10.1300/j025v02n01_09.

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45

Ayersman, David J. "Effects of Computer Instruction,." Computers in the Schools 12, no. 4 (December 30, 1996): 15–30. http://dx.doi.org/10.1300/j025v12n04_03.

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46

Kearsley, Greg. "Networking computer based instruction." Education and Computing 1, no. 2 (April 1985): 109–16. http://dx.doi.org/10.1016/s0167-9287(85)93794-x.

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47

Desch, Larry W. "Pediatric Computer-Assisted Instruction." Archives of Pediatrics & Adolescent Medicine 149, no. 3 (March 1, 1995): 303. http://dx.doi.org/10.1001/archpedi.1995.02170150083015.

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HICKS, JAMES O., SAM A. HICKS, and TARUN K. SEN. "Learning spreadsheets: human instruction vs. computer-based instruction." Behaviour & Information Technology 10, no. 6 (November 1991): 491–500. http://dx.doi.org/10.1080/01449299108924306.

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McNeley, Kevin, and Veljko Milutinovic. "Emulating a Complex Instruction Set Computer with a Reduced Instruction Set Computer." IEEE Micro 7, no. 1 (February 1987): 60–72. http://dx.doi.org/10.1109/mm.1987.304939.

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Dirkx, Erik. "CRISC Configurable Reduced Instruction Set Computer or Complex Reconfigurable Instruction Set Computer." Microprocessing and Microprogramming 23, no. 1-5 (March 1988): 239–41. http://dx.doi.org/10.1016/0165-6074(88)90362-6.

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