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Lecture-based teaching paired with laboratory-based exercises is most commonly used in cybersecurity instruction. However, it focuses more on theories and models but fails to provide learners with practical problem-solving skills and opportunities to explore real-world cybersecurity challenges. Problem-based Learning (PBL) has been identified as an efficient pedagogy for many disciplines, especially engineering education. It provides learners with real-world complex problem scenarios, which encourages learners to collaborate with classmates, ask questions and develop a deeper understanding of the concepts while solving real-world cybersecurity problems. This paper describes the application of the PBL methodology to enhance professional training-based cybersecurity education. The authors developed an online laboratory environment to apply PBL with Knowledge-Graph (KG) based guidance for hands-on labs in cybersecurity training.Learners are provided access to a virtual lab environment with knowledge graph guidance to simulated real-life cybersecurity scenarios. Thus, they are forced to think independently and apply their knowledge to create cyber-attacks and defend approaches to solve problems provided to them in each lab. Our experimental study shows that learners tend to gain more enhanced learning outcomes by leveraging PBL with knowledge graph guidance, become more aware of cybersecurity and relevant concepts, and also express interest in keep learning of cybersecurity using our system.
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Comparing How Different Inquiry-based Approaches Impact Learning Outcomes
To date, there are currently many variations of inquiry-based instruction including problem-based learning (PBL), lecture prior to problem solving, and case-based learning (CBL). While each claim to support problem-solving, they also include different levels of student- centeredness and instructor support. From an educational perspective, further clarity is needed to determine which model best supports learning outcomes such as conceptual knowledge, causal reasoning, and self-efficacy. While various meta-analyses have been conducted to ascertain how inquiry-based instruction compares with lecture-based approaches, there are few studies that directly compare these methods. To address this gap, this study looked at the effects of PBL, lecture prior to problem-solving, and CBL on students conceptual knowledge, causal reasoning, and self-efficacy (N = 91). While no significant difference was found on self-efficacy, the results found that learners in the PBL group performed highest on conceptual knowledge. In terms of causal reasoning, the PBL group outperformed other conditions on correctly identified connections. However, the PBL condition also had the highest number of incorrectly identified concepts. Implications for theory and practice are also discussed.
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- Award ID(s):
- 1918751
- PAR ID:
- 10207682
- Date Published:
- Journal Name:
- Interdisciplinary Journal of Problem-Based Learning
- Volume:
- 14
- Issue:
- 1
- ISSN:
- 1541-5015
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract BackgroundUsing simulations in science instruction can help make abstract topics more concrete and boost students' understanding. AimsThe current research examined whether using a simulation as an exploratory learning activity before an accompanying lecture has additional learning and motivational benefits compared to a more common lecture‐then‐simulation approach. SamplesParticipants (Experiment 1,N = 168; Experiment 2,N = 357) were undergraduate students in several sections of a first‐year chemistry course. MethodsStudents were randomly assigned to explore a simulation on atomic structure either before a lecture (explore‐first condition) or after the lecture (instruct‐first condition). In Experiment 1, the simulation activity time was limited (15 min) and the activity varied in whether self‐explanation (‘why’) prompts were included. In Experiment 2, the activity time was lengthened (20 min), and only ‘why’ prompts were used. After the activity and lecture, students completed a survey and posttest. ResultsIn Experiment 1, students in the explore‐first condition scored lower on posttest conceptual knowledge scores and reported lower curiosity compared to students in the instruct‐first condition. Scores for basic facts and transfer knowledge, and self‐reported situational interest, self‐efficacy, and competence, were equal between conditions. No effects of prompt condition were found. In Experiment 2, with longer activity time, the results reversed. Students in the explore‐first condition scored equally on basic facts and higher on conceptual knowledge and transfer measures, while also reporting higher curiosity, situational interest, self‐efficacy, competence, and cognitive engagement. ConclusionWhen properly designed, placing simulations before—rather than after—lecture can deepen learning, motivation, and competence.more » « less
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This research work in progress research paper examines student perceptions after completing an exploratory learning lesson before instruction on an introductory programming concept. During exploratory learning activities, students explore a novel concept prior to instruction—the reverse of typical instruct-then-practice methods. Exploratory learning before instruction can help students activate prior knowledge, become aware of their knowledge gaps, and discern important problem features to improve conceptual understanding. Students in a first-year engineering course (N=402) learned about Python error messages in one of two conditions. In the explore-first condition, students completed a collaborative activity prior to instruction. In the instruct-first condition, students received instruction prior to the activity. Following the activity and instruction, students completed a survey to assess their perceptions of the activities. Survey items (e.g. cognitive load, self-efficacy, belonging, knowledge gaps) were chosen as potential factors that could explain learning outcomes between the two conditions. In prior work, we found higher posttest scores in the instruct-first compared to explore-first condition, contrary to the majority of previous studies. Cognitive load and knowledge gaps were higher in the explore-first condition than the instruct-first condition. Self-efficacy and competence were lower in the explore-first condition. No other significant differences were found. Exploring before instruction might disrupt learning and perceived efficacy and competence if the activity is too challenging, or if the instruction does not fully resolve gaps in students’ knowledge.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.14434/ijpbl.v14i1.28624
