Interactive instructional teaching method (IITM); contribution towards students’ ability in answering unfamiliar types questions of buffer solution

1.1 Defining adversity quotient and learning interest

Adversity Quotient is an internal factor affecting students’ success in learning (Suryadi & Santoso, 2017). It is related to how a person reacts, addresses an obstacle, and attains achievement based on their response to the challenges they confront (Akbar et al., 2023; Juwita et al., 2020). Teacher knowledge concerning the adversity quotient of their students is essential for several reasons. A study on Thai university students demonstrated a positive correlation between students’ adversity quotient and their health behaviour (Choompunuch et al., 2021). Several studies have been conducted to find the role of adversity quotient in life satisfaction (Zhao et al., 2021). However, studies concerning the correlation between students’ adversity quotient and achievement still presented unsatisfactory outcomes. Matore et al. (2015) revealed the small contribution of adversity quotient to the achievement of Malaysian vocational students. Therefore, they encouraged future studies in this area. Another study uncovered a strong correlation between students’ adversity quotient, teacher professionalism, and self-regulated learning (Saguni et al., 2021). Our review found limited works in revealing the relationship between adversity quotient and students’ ability to a particular science and chemistry concepts.

Many students consider science disciplines, including chemistry, uninteresting subjects (Musengimana et al., 2021). Aside from insufficient teaching media and ineffective teaching approaches, negative attitudes and interest in chemistry are believed to be critical factors concerning students’ low achievement in chemistry (Cheung, 2009; Khan & Ali, 2012). Attitude represents students feeling, beliefs and individual values toward science (Hacieminoglu, 2016). In a broader context, the values and perspectives held by educators play a significant role in shaping the methods they employ in the classroom (Hofer & Lembens, 2019). Interest is a phenomenon that arises due to an individual’s interaction with specific objects and is typically characterised by positive feelings and attention (Renninger & Hidi, 2011). Regarding learning, interest is defined as an experiential state characterised by attention, effortless engagement, and pleasant feelings (Green-Demers et al., 1998; Wiśniewska, 2013). Studies examine the relationship of learning interest with other learning outcomes, including flow and creativity (Dan, 2020), chemistry level achievement and gender (Cheung, 2009), cognitive certitude (Hong et al., 2019) and other aspects. Knowledge of students’ learning attitudes towards chemistry will be a consideration factor for educational policymakers (Habiddin et al., 2020).

1.2 Interactive instructional and its potential support for students’ deep understanding

The high quality of chemistry teaching can be achieved by providing a good teaching and learning environment that leads to optimal chemistry concept acquisition. Students’ understanding of chemistry must be accompanied by a higher level of thinking to survive in this competitive era. A meaningful teaching strategy that drives students to construct their knowledge actively should be advocated for promoting students’ understanding, argumentation skills and ability to deal with high-level questions. Employing an innovative teaching strategy can improve students’ high level of thinking (Saepuzaman et al., 2021). Hofer & Lembens (2019) employed inquiry-based learning to enhance teachers’ attitudes.

In this study, we employed interactive instructional teaching methods to promote students’ ability to solve unfamiliar questions. An interactive instructional is a teaching approach we developed in basic chemistry I & II classes at the Universitas Negeri Malang. This approach has been applied since 2019. As stated by Holdsworth and Thomas (2021), employing a new teaching strategy leads to a potency for promoting students’ critical thinking. The theoretical frameworks for this approach cover active learning, discovery learning, and cooperative and collaborative learning (Ulfa et al., 2021). Our initial review suggests that the approach can build students’ higher levels of thinking (Ulfa et al., 2021). The syntax of IITM involves peer discussion, brainstorming and arguing to support their answer, which are essential supplements for building students’ high level of thinking, leading to an ability to answer unfamiliar questions successfully. Evidence shows that arguing between students ignites students’ argumentation skills (Larrain et al., 2021). Therefore, a teaching approach accommodates particular concepts’ characteristics, pedagogical aspects and learning environment is highly advised. The teaching model applied in this study will be an additional reference for chemistry educators in delivering effective chemistry teaching, particularly for buffer solutions.

2.1 Intervention procedure (IITM vs. DITM)

IITM and DITM in experimental and comparison groups were implemented in the same learning environment, except for the teaching method. One of the authors took the role of the teacher for both groups with the school’s permission and the actual chemistry teacher at the school. To avoid an implementation threat, some members of the experimental group may receive benefits from the study’s procedures that were not planned for (Fraenkel et al., 2011), all the variables (duration for each meeting, the frequency of meetings in a week, handout, and set of assessments) are the same for both groups, except for the teaching method. In addition, the researcher, who is also the teacher’s role, is highly encouraged to deliver the teaching procedure to the two groups optimally. Table 1 summarises the differences in learning syntax between the two teaching strategies.

2.2 Instrument and data analysis

A typical 10 unfamiliar types of questions were applied to investigate students’ achievement of buffer solutions. We categorised the questions as unfamiliar-type questions since they were portrayed in a more difficult format than the questions commonly provided by their teachers. However, the challenges harboured in answering those questions have yet to be in the Higher Order Thinking Skills (HOTS) category for several reasons. The format of the questions was multiple choice, and the limited pictorial aspects or similar features demanded a higher level of thinking. Before data collection, a chemistry staff and school teacher validated the instruments (content, depth and sequence, and their relevance to high school chemistry level). All the feedback from the two validators has been taken into account to form the final instrument. Some high school students were also invited to provide feedback regarding familiarity with the language. Construct validity was also performed before the instruments were used for data collection. All the items were found to be valid. The reliability index of the instruments was 0.836, falling into the “very high” category. The complete instruments are available on request.

Figure 1 provides an example of a familiar type of question. This question required students to determine the region of buffered solutions from four ranges. Why is this question considered as an unfamiliar one? Teachers commonly provide an algorithmic question on how to show that the pH of a buffer solution can be maintained with a small additional concentration of acid or base. Instead, this question demanded students to analyse the range in the graph representing a buffered region. Students’ understanding of how the buffer solution works will be valuable to correctly determining the correct choice.

Figure 1:

Example of the unfamiliar type of question.

A questionnaire was used to measure students’ adversity quotient and learning interest. Students’ adversity quotient was measured according to four components, CORE: control, origin & ownership, reach, and endurance (Stoltz, 2010). Meanwhile, students’ learning interest in chemistry was revealed from six indicators: attention to chemistry, motivation to learn chemistry, necessity feeling to chemistry, joy in learning chemistry, teaching aids effect, and participation in chemistry class. The instruments are available in the appendices. The questionnaire was validated using a reverse translation procedure to ensure that the Indonesian version keeps the meaning of its original language (English). The reverse translation procedure means that the Indonesian translation version from the authors was re-translated into English by two experts. The two experts (validators) re-translated the manuscript without seeing its original questionnaire. The re-translated result from the two validators was compared to the original version. The similarity in meaning between the original and re-translated versions ensures that the Indonesian version keeps the original meaning of the original questionnaires.

Table 2 provides some examples of how the reverse translation procedure works. The statements in the “original version” column are the actual statements in the English version. Those in the “Translation (Authors)” column are the translated versions given to the students (respondents). While those in the “Re-translated (validator)” are re-English translations from the validator that build upon the statements in the translated version in the middle column without looking at the original version statements. The exact meaning between the original and re-translated versions implies that the translated version was valid.

Statistical procedures, including Analysis of variant (ANOVA), t-test, and descriptive statistics, were applied to measure the difference in students’ achievement of buffer solution, adversity quotient, and learning interest between the two groups.

3.1 Description of students’ prior understanding, learning interest, and adversity quotient before intervention

Before intervention (the implementation of IITM and DITM), students’ prior ability on unfamiliar types of questions, learning interest, and adversity quotient were measured. Therefore, the improvement of the three variables after the intervention will be uncovered clearly. The questionnaire used for revealing students’ adversity quotient and chemistry learning interest before and after the interventions are the same. The level of adversity quotient and chemistry learning interest between the two groups of students was found to be equal. Meanwhile, students’ prior ability on unfamiliar types of questions was measured using a typical unfamiliar type of question of acid-base. Before the intervention, the number of IITM and DITM students who could answer typical unfamiliar types of questions correctly was 31.03 % and 45.16, respectively. The gap reflects that the IITM students demonstrated a better initial ability to solve a typical unfamiliar type of question than the DITM students. Due to this difference, the different impact between IITM and DITM on students’ ability to solve the unfamiliar type of question was described based on the relative improvement of each group in answering those typical questions before and after the interventions.

The average score of adversity quotient for IITM students was 71.86 and 69.51 for DITM students. For the learning interest, the average score for DITM students was 66.28, while the DITM students were 63.90. These scores show that both groups of students exhibit an equal initial adversity quotient and learning interest before intervention.

3.2 Description of student’s ability to solve the unfamiliar type of question, learning interest, and adversity quotient after intervention

The number of students providing correct answers after intervention for IITM and DITM students, in general, is described in Table 3. Regarding properties of buffer solution, the number of IITM students selecting correct answers is significantly higher than the number of DITM students with more than 10 % gaps. Meanwhile, the DITM students demonstrated slightly better performance on the topic of the curve of titration and pH of the buffer solution. In general, the number of IITM students selecting correct answers is slightly higher than those of DITM students.

Although the difference between the two groups is insignificant, some discrepancies in students’ scientific explanations to support their answers are observed, as indicated by their answers to the question in Figure 2.

Figure 2:

Example of the unfamiliar type of question for IITM and DITM students.

Figure 2 is categorised as an unfamiliar type of question for Indonesian secondary school students. Primarily, the most common question in buffer solution teaching to measure students’ mastery of buffer capacity is how to calculate the pH of a buffer solution after adding a small amount of base or acid. Students commonly used mathematical operations to answer such types of questions.

The example of an IITM student’s response to question Figure 2 is provided in Figure 3, and DITM students for Figure 4 (both in the Indonesian language) and the English translation is provided in italic font within this paragraph. Both groups of students correctly recognise that the pH for both solutions is the same, but Y will have a higher buffer capacity. An example of a difference in terms of the level of student’s answers from the two groups answering the question is indicated in Figures 3 and 4. The IITM student (Figure 3) provided a deeper explanation that an equal comparison between acid and its conjugation for the two solutions will result in the same pH. However, a 1:1 ratio for the X solution and a 2:2 ratio for the Y solution result in a more extensive buffer capacity for the latter solution. Meanwhile, the DITM student (Figure 4) only selected the correct answer without providing a supporting argument. This phenomenon indicates the superiority of DITM students’ ability to answer an unfamiliar question.

Figure 3:

Example of an IITM student’s answer to the question in Figure 2.

Figure 4:

Example of a DITM student’s answer to the question in Figure 2.

The average number of DITM and IITM students answering the unfamiliar type of question after the intervention was equal to 48.47 and 47.40, respectively. However, considering that the initial number of successful students before intervention for IITM students is significantly lower than that for DITM students, the IITM could promote a better impact on student’s ability to solve unfamiliar questions. IITM students gained about 17 % points improvement, while the DITM students were relatively stagnant.

This result confirms the better contribution of IITM towards students’ achievement of buffer solutions in comparison with the DITM. IITM allow students to engage actively in a group discussion with their groups and within the class. They explored an open-ended question logically, promoting a high achievement of buffer solution.

Although the adversity quotient of the two groups after treatment fell in the moderate category (Table 4), IITM students consistently demonstrated superiority over the DITM students in each indicator of adversity quotient. The highest gap between the two groups was observed for the “react and endurance” indicators. The statistical procedure of the t-test confirmed the difference between the adversity quotient scores of the two groups. This result implies that IITM improves students’ adversity quotient better than the DITM.

Table 5 shows the difference scores in students’ learning interests between the two groups in each indicator. As for the adversity quotient, students’ learning interest between the two groups fell in the moderate category for each indicator. However, the scores of learning interest for IITM students are higher than those for DITM students in all indicators. Joy in learning chemistry and motivation to learn chemistry is the highest difference gap between the two groups. The scores for all indicators confirm that IITM improves students’ learning interest with a higher effect compared to DITM. The t-test also confirmed the difference. The better learning interest of IITM students in chemistry compared to the interest of DITM students may explain the better ability to the unfamiliar type of questions for the former group. Positive learning interest drives other students’ positive attitudes toward learning, including learning motivation (Herpratiwi & Tohir, 2022). A similar study uncovered students’ confidence in their understanding of chemical kinetics (Habiddin et al., 2020).

3.3 Correlation of students’ adversity quotient and learning interest towards students’ ability to answer unfamiliar types of questions

The correlation between students’ achievement of buffer solution and their adversity quotient was measured using a bivariate Pearson correlation question and found a positive correlation between the two variables. The value of r _calculation (0.188), which is higher than the r _table (0.179) with the sign-2-tailed of 0.04 < 0.05 confirm the correlation (Table 6). The positive correlation implies that the students’ adversity quotient increases with the increase in students’ achievement of buffer solutions. Previous studies demonstrated the correlation between adversity quotient, students’ health behaviours (Choompunuch et al., 2021), and life satisfaction (Zhao et al., 2021).

A similar correlation was also found between students’ learning interest and their adversity quotient. The value of r _calculation (0.298), which is higher than the r _table (0.179) with the sign-2-tailed of 0.010 < 0.050 confirm the positive correlation. Meanwhile, no evidence supports that students’ learning interests and adversity quotient affect students’ achievement of buffer solutions. We realise that some technical aspects, including internet connection, may hinder the result of this study. At some points, students’ online discussions were interrupted during the implementation of IITM due to the instability of students’ internet connection.