At-Risk Students and Technology Education:
For quite some decades, technology has shaped the landscape of education in an unprecedented manner; thus, paving the way for researches along this line vis-a-vis- other personal and non personal variables. The bottom line is how to improve academic performance of children by and through educational technologies.
In 2000, Philipp Cardon’s (p.49) study admitted a resurgence of interest on vulnerable students which he termed as “at-risk.” Various studies were conducted and focused on the said subject matter as evidence by literatures; and their researches focused on vocational training, meeting this student’s needs through interesting curricula.
What is an ‘at-risk’ student? Cardon (2000, p.50) defined “at risk,” using three guide- post, namely: failing to achieve educational goals as a result of lack of the necessary skills and knowledge to be a productive members of society; children demonstrated behavioral issues interfering with the aims of educational goals; and those children whose family background were characterized by poverty, and non-English native speakers. Cardon added that, the Taylor-Dunlop and Norton’s study showed that at-risk students have the desire to attend math and hands-on courses like art.
Finally, Cardon advanced that “although centered on a curriculum of construction, manufacturing, communication, and transportation/power/ energy, technology education courses are similar to art courses because they focus on teaching students through hands-on activities.”
The Research Purpose & Hypotheses
It was in this regard that Cardon’s qualitative case study was to explore, describe, and examine how at-risk students experience and interact with the technology education curriculum.
Philipp Cardon’s (2000, p.51) research paper hypothesized that technology education indeed attracts “at-risk” students, but, it cannot be negated though this concept of educational technologies have gained little attention regarding their “influence’ to this type of students. Also, there were no studies conducted on student’s (at-risk) views on educational technology as a tool and their desire to take this educational technology courses. Finally, the study also explored the importance of the above stated technologies in their continued presence in school. Thus, as a qualitative case study it was to explore, describe, and examine how at-risk students feel, understand and relate with the technology education curriculum.
Thus, with the above suppositions, Cardon’s hypotheses are as follows: “How do at-risk students respond to a technology education program?” and “Why do at-risk students enroll in technology education courses?”
The Research Context
Cardon’s (2000) research context hinged on the three primary learning theories affecting technology education environment, namely: construction of knowledge, problem solving, and hands-on learning theories. As an important part of education, construction of knowledge learning theory argued that “what is internalized is not the behavior but, the system that organizes the specific acts involved.” It was believed that the cognitive based theory instruction design shifted the focus from passive to active content acquisition—assisted the students to construct meaning and not otherwise. With regard to problem-solving learning theory, it important role in the contemporary technology education curriculum can not e over-emphasized. This theory consists of “cognition, guided practice, and automated behavior stages of expertise in problem solving;” thus, students achieved educational learning as well as satisfaction using technology driven curriculum. Lastly, the hands-on learning theory postulated that students should interact with their learning environment. This theory was postulated on the premise of the fact that student learn by their involvement and experience in the world which occur when the mental activity is combined with physical action,
The Research Methodology
Cardon’s (2000, p. 51) research method employed a case study approach--the participant-observation qualitative research methodology. A pilot study was performed to generate data for observation and the development of questions needed by the study, as well as to determine some views of “at-risk” and their environment, with regards to educational technology. Along this line, he employed a purposive sampling. The study main location was different from that of the pre-study. The stated location was supported by an educational technology program. “The eight at-risk student participants in the study were chosen from a survey of technology course and a power/energy/transportation course containing mostly at-risk students. If the student in question demonstrated most of the characteristics listed by [protocol,] then, he or she was considered a possible candidate for the study.”
Now, Cardon (2000, p. 52) referred to the data as evidence. In his evidence gathering, he used two procedures namely: interactive methods (participant’s observation and interviews) and non-interactive method (document evaluation). Also, member checking and the establishing of credibility through patters were employed “to counteract the novelty effects and observer bias.” These methods helped him in triangulating the evidences he used in this study.
Since, the researcher primarily used a qualitative research methodology, then, it was but proper to employ the above mentioned triangulation techniques, as well other techniques such as member checking and establishing credibility so as to enhance the reliability of the instruments and protect data integrity as in this instance called “evidences.” This is a proper methodology and safety measures in a qualitative research.
On the area of credibility of this qualitative case study, three factors were present: “firstly, the study was performed over a six-month period of time; secondly, intense observation and evidence collection was performed once the subjects were identified and secured; and lastly, evidences from observations, interviews, and document evaluation were used to help support the trustworthiness of the findings.”
This research article set forth evidence evaluation procedures. Using the “NUD*IST(r)”, software was used to search for emerging themes and compile the evidence according to these themes. The three categories, construction of knowledge, problem solving, and hands-on learning, became evident.
The Research Purpose & Results
Having said these arguments, the above methodologies have indeed achieved the aims of the study which are “to explore, describe, and examine how at-risk students experience and interact with the technology education curriculum.”
Construction of knowledge Part of the curriculum: As a theoretically-based study, Cardon ’s (2000 p. 52-55) study’s result revealed that the “evidence, evaluated according to the construction of knowledge, problem solving, and hands-on learning theories, contained consistencies found among the at-risk students.” The study indicated the presence of the “construction of knowledge as a part of the curriculum in helping the at-risk students to learn the concepts regarding planning, materials, and processes, and to give the students the experience of working with these concepts.” Cardon admitted that the evidence presented, supporting the problem-solving theory was as consistent as he hoped to be, though the evidence of construction of knowledge or hands-on learning theories showed and demonstrated the importance of learning the concepts of planning, materials, and processes. It was revealed that “at-risk” students “learned better through hands-on learning methods than through book-work or lecture methods.” There was consistency found between the at-risk students in both the construction of knowledge and hands-on learning theories.
Knowledge and Problem-Solving Theory: The data revealed the presence of a relationship between the construction of knowledge theory and the problem-solving theory---“the knowledge of planning, materials, and processes was vital for the success of students in problem-solving activities.” As a result, students gained new perspective and knowledge as they face and tackle the problems at hand. Also, relationship was presence between the problem-solving theory and the hands-on learning theory as students under educational technology curriculum were required to work interactively with tools, planning, materials, and processes as they solve problems. The study further revealed that “knowledge construction for students in the technology education program involved the use of hands-on methods in order to learn how to work with the materials and processes of industry.” Integration of knowledge between knowledge construction subjects greatly influenced the technology education program and assisted the students to understand mathematics and science concepts.
Finally, Cardon (2000) revealed that the “at-risk” students found school to be boring and academically focused. In spite of this revelation, these “at-risk” students believed that there is success, achievement and hope for them in an educational technology- driven curriculum.
The Study’s Implication
On the study’s implication, “at-risk” student’s teachers should by all means include hands-on and problem-solving learning methods in their curriculum in order to allow these students reached their potentials and became partners of development of the community. Curriculum planners and developers should include hands-on learning theory in the “curricula that they will develop in order to assist at-risk students in learning the material and performing better in the courses.” Mathematics, science, and technology education’s integration is a welcome initiative in curriculum planning.
Value Added to Education
It is in this regard that this research, though has some limitations like all other researches, has bolstered that there is hope for “at-risk” students. The present research has added value to the ever glowing literature on the efficacy and effectiveness of technology in delivering better understanding to the vulnerable students such as at risk students. This type of students will succeed well with proper curricula developed and integrated with educational technology driven approaches.
After all, educational and curriculum planners should bear in mind that the very aim of education is to prepare students to respond appropriately to the challenges they face everyday. That is, education for life long learning.
Learners: Would Technology Help?
K. A. Edmonds
The 21st century is an era where technology permeates the fabric of almost all sectors of our society. It is so pervasive that man could not do otherwise, but embrace it. In educational sector, the educational planners and curriculum redevelopers has found a new ally in improving student school/academic performance through a technology driven approaches and learning environment.
Li Qing & Edmonds (2005) were both of the opinion that, as far as mathematics teaching and learning is concerned, technology driven approaches influences and enhances their performance. This was in accord with the adage that “the new trend in education that emphasizes the importance of learning with technology instead of learning from technology.” Thus, an integrated model of mathematics learning is a must. For Li Qing & Edmonds (2005), there is a need for “technology to be appropriately integrated into student regular mathematic learning;” and not only on the regular students, but to the struggling, at-risk learners. For Li and Edmonds, computer-assisted instruction to the at-risk learners improves their educational performance rather than just assisting. Since there are few researches along this line, the duo deemed it fit to investigate the effect of technology on improving achievement of at-risk adults and how to further improve this method of instruction.
The Research Purpose & Hypotheses
Li Qing & Edmonds (2005) study was aimed at examining the “effects of computer-assisted instruction (CAI) on adult at-risk learners in their fundamental mathematics education. The study specifically, sought to answer whether adult learners with learning disabilities improve their level of achievement in mathematics studies by engaging in computer-assisted instructions (CAI) or not; what benefits and advantages emerged when using CAI with at-risk learners; and what limitations and challenges were identified when using CAI with at-risk learners?”
Li and Edmonds defined CAI as those tutorials or simulation activities supplementing teacher-directed instruction. It is a blended approach of instruction using technology and classroom-based learning.
The Research Context
Li and Edmonds (2005, p. 146) hinged his research context on the cognitive and behavioral psychology and how these might be of help in building the computer-assisted instruction for at-risk learners. They both agreed that the “behavioral theories of instruction considered student learning behaviours as predictable” which impact a specific stimulus and response when used in curriculum development as espoused by Gagne. On the other hand, cognitive theorist pointed out “complex factors that mediate between stimulus and response, such as individual mental processes.” It is in this regard that understanding the uniqueness of an individual plays an important role in improving learning as well as designing it. Having these things in mind, their will be mastery leaning as well a learning environment that is open to diversity in learning styles and outcomes.
The two theories: The paper of Li & Edmonds stated two theories such as that of Bloom’s (1971) Learning for Mastery theory, which provided “practical guidelines for our design of the initial stage of learning.” Bloom further added that “if given enough time, 95% of all students will gain mastery of a subject.” Also, was “Scaffolding” techniques which used learning to supports and promote cognitive development? It is a temporary framework supporting learners’ performances beyond their capabilities. Having said these things, the two theoretical foundations, is based on the principles of behaviouralism and cognitivism; thus, educators can provide instruction that is parceled for mastery and individuality at the same time.
The Instrument and its Validity: As an experimental model, this present research employed a case study nested within a qualitative and quantitative data. According to Li & Edmonds (2005) study “mixed method approach advocates ‘one method … nested within another method to provide insight into different levels or units of analysis,’ thereby drawing on all possibilities.” Also, the current study used qualitative approach which the quantitative data cannot address. The participants were purposively selected “for their unique setting and characteristics as compared to average, mainstream students. It was decided to compare three classrooms of at-risk adult learners studying basic mathematics. The samples were from an adult high school in Western Canada which was enrolled in an Adult Basic Education (ABE) program. Learners in this sample, struggled with learning and academic achievements throughout their life, and had entered a number of learning programs in the past, usually without success.” The administered tests were both online and paper-based. The paper-based tests were a course pre-assessment test, monthly unit tests, and the final examination while the online tests were a monthly pre/post-test that focused on one topic within a unit.
The test statistics used.: The study used t-test for quantitative data and for qualitative analysis, the “data were placed into digital form in a word processor, and organized into categories such as objective of the lesson, student reactions, noted impact, problems, and lesson changes for the technology-based class.” As to the question of reliability “all the correlations were statistically significant at the .001 level. There were strong correlations among all scores, with the smallest correlation coefficient being .58. This showed that the reliability of each testing instrument was high.”
The credibility of the two methods: The use of both quantitative and qualitative data erased doubts as to the questionnaires or instruments’ validity and reliability. The quantitative part of the research erased the biases inherent in the qualitative data; thus, for all intents and purposes, this research was a strong one in terms of credibility and liability.
The use of pre and post test played an important role in erasing the perceived biases of the instruments. The paper showed that as far as the reliability issue of this experimental study was concerned, it was statistical significance at .001 alpha levels.
Having said these things, the aims of the project was achieved and the research’s integrity was even bolstered.
The Research Findings
Li & Edmonds’ (2005, p. 163) study showed positive results and revealed that Computer Assisted Instruction CAI), has the potential for an effective and positive method in teaching mathematics for at-risk learners. Also, the said educational technology approach showed “some positive gains in various achievement tests as well as increased student confidence and satisfaction with mathematical learning. In addition, CAI provided alternative learning resources that can better address diversity in language abilities, disabilities, skill levels, and learning styles among this population.”
The Study’s Implication & the Value Added to Education
The study strongly implied that educational technology as a mode of instruction holds a promise and potential for CAI for teaching mathematics to at-risk learners.
Also, the value of CAI to educational community was unprecedented, such that even the findings of this present research showed us of in crease in self-confidence and satisfaction towards learning mathematics.
Further, Li & Edmonds (2005, p 163) stated that building of knowledge through increased practice and learning with online and computer-based lessons is an effective venue for learning. Also, designing scaffolded learning in digital environments and with the presence of continual teacher-support, learners overcame learning difficulties, and became more satisfied with their learning.
Finally, indeed technology has added value to the growing educational technology which is used as a potent tool for delivering educational materials effectively and efficiently to its students and audience. Over time, it has proven its worth to change and has transformed lives of people whom years ago, learning was difficult to impact.
Cardon, Philip (2000). At-Risk Students and Technology Education: A Qualitative Study
Journal of Technology Studies. Winter-spring 2000, pp-49-57
Kervin, L., Vialle, W., Herrington, J. & Okely, T. (2006). Research for Educators. Melbourne: Thomson/Social Science Press
Li Qing & Edmonds K. 2005. Mathematics and At-Risk Adult Learners: Would Technology Help? Journal of Research on Technology in Education. 142-166, Winter 2005: Volume 38 Number 2