This innovative practice WIP paper describes a novel metric for evaluating students' communication skills in engineering technology programs and provides guidance of how to improve them further. The ultimate objective of any academic engineering program is to prepare students to be ready for future industrial roles and challenges. According to the Engineering Competence Model [1]which was released by the American Association of Engineering Societies and the Department of Labor, this model describes the engineering competence that includes the personal effectiveness competencies, academic competencies, workplace competencies, industry-wide competencies, and industry-sector competencies. On one hand, the Zoomers (Generation Z) were born during the peak of internet and connectivity revolution era and live with tendency to and dependency on virtual sphere. Thus, this might be problematic once those students move to the next phase of their lives and commence their industrial career where performing different tasks requires excellent communication skills and involves full engagement in teamwork, client surveys, and feedback. On the other hand, the engineering technology workplace hosts a wide array of professionals who may be inhomogeneity and/or different in one way or another. Effective communication skills entail meticulous attention to details across all aspects, including forms, style, and context of communication, such as, high context vs low context communication, introvert vs extrovert communication, one directional vs rhetorical communication, virtual vs face-to-face communication, hierarchy communication consideration, and human factors (for example, emotions and psychology) vs machine factors. Thus, gaining informative awareness about all these topics is significantly beneficial. The main goal of this research is to develop an evaluation metric that can be systematically used to continuously assess and develop the students' communication skills in the Engineering Technology programs. The proposed metric may include self-reported surveys and/or structured case scenarios interviews. In addition, the integration and utilization of the gained skills will be investigated, and the best practices shall be recommended. These practices will be shared with the workforce and their feedback sought for further refinement.

This research WIP paper describes the current workforce needs of math skills. In today's rapidly evolving technological landscape, understanding the mathematical requirements of the engineering workforce is essential for educational institutions and industry stakeholders alike. This study outlines a comprehensive survey-based study aimed at identifying the current and future mathematical needs of engineers in the workforce, while considering the impact of artificial intelligence (AI) on these requirements. The study will involve administering a survey to practicing engineers to gauge their utilization of mathematics in their respective fields. Questions will delve into areas such as the types of mathematical concepts commonly employed, the most complex problems encountered, and any gaps in mathematical education that have been observed. Furthermore, the survey will seek insights into potential training needs to enhance mathematical skills among professionals. One of the primary objectives of this research is to provide valuable insights into the current state and future perspectives of the workforce's mathematical requirements. By analyzing survey responses, the study aims to offer recommendations to educational institutions to align their curricula with the evolving needs of industry. This proactive approach will ensure that future generations of engineers are equipped with the necessary mathematical competencies to thrive in their careers. A key aspect of this study is the differentiation between engineering and engineering technology disciplines, recognizing that mathematical requirements may vary across different sectors. By delineating these distinctions, the research will provide targeted recommendations tailored to the specific needs of each field for two year and four years institutions. Collaboration with national and international organizations, including IEEE, ASEE, STEM Pioneers and other platforms, will ensure a broad and diverse participation pool for the survey. This strategic partnership will facilitate access to a wide audience of professionals, thereby enhancing the validity and reliability of the study outcomes. In conclusion, this survey-based study represents a concerted effort to comprehensively understand and address the mathematical needs of the current workforce, particularly within AI-driven engineering environments. By bridging the gap between academia and industry, the research aims to foster a symbiotic relationship wherein educational institutions adapt their offerings to meet the demands of the evolving job market, heavily influenced by the pervasive integration of AI technologies. With meticulous data analysis and strategic collaboration, the study anticipates yielding actionable insights that will not only shape the future of mathematical education but also contribute significantly to professional development in engineering and engineering technology fields amidst the omnipresent influence of AI.

When teaching a fundamental course in Electronics, new concepts are introduced to students, and they are required to learn and apply new mathematical formulas while being shown many examples. However, these new concepts and ideas can be challenging and hard to comprehend. In order to stimulate students' eagerness to learn new concepts further and to reinforce a clear and solid understanding of the new topics, a problem-based approach with the Think-Pair-Share method is incorporated in the classroom. By adopting this approach, students are encouraged to actively engage in problem-solving activities, which enhances their critical thinking skills and ability to apply concepts learned in class. The Think-Pair-Share method allows students to collaborate in pairs or small groups to analyze problems and share their insights with the class. A student-centered learning environment is promoted through this approach, allowing them to develop their problem-solving skills and learn from their peers' experiences. Furthermore, it has been confirmed by the students' survey results that the implementation of these teaching methods in Electronics is balanced with the class time. Additionally, a significant number of students have recommended that the TPS and problem-solving methods be continued by the instructor(s) in this class or other future Electronics classes. The results of this study demonstrate the effectiveness of this approach in teaching relatively challenging electronics topics to students.